Method for Delivery of an Encoded EMS Profile to a User Device

ABSTRACT

The current invention describes a method and system for imposing a dynamic sentiment vector to an electronic message. In one embodiment of the invention, the method comprises of receiving a text input comprising message content from an electronic computing device associated with a user. The message content is further parsed and comprised in the text input for emotionally-charged language, assigned a sentiment value, based on the emotionally-charged language, from a dynamic sentiment value spectrum to the text input. Additionally, based on the sentiment value, imposing a sentiment vector, corresponding to the assigned sentiment value, to the text input, the imposed sentiment vector rendering a sensory effect on the message content designed to convey a corresponding sentiment.

TECHNICAL FIELD

This invention relates generally to the field of electroniccommunications and the transmittance of such communications. Morespecifically, the invention discloses a new and useful method fordelivering a therapeutic through an eco-system of digital content basedon a user-mapped EMS.

BACKGROUND

In the past few decades, the availability and use of electroniccomputing devices, such as desktop computers, laptop computers, handheldcomputer systems, tablet computer systems, and cellular phones havegrown tremendously, which provide users with a variety of new andinteractive applications, business utilities, communication abilities,and entertainment possibilities.

One such communication ability is electronic messaging, such astext-based, user-to-user messages. Electronic messaging has grown toinclude a number of different forms, including, but not limited to,short message service (SMS), multimedia messaging service (MMS),electronic mail (e-mail), social media posts and direct messages, andenterprise software messages. Electronic messaging has proliferated tosuch a degree that it has become the primary mode of communication formany people.

While electronic messaging can be a particularly efficient mode ofcommunication for a variety of reasons—instant delivery, limitlessdistance connectivity, recorded history of the communication—electronicmessaging does not benefit from the advantages of in-personcommunication and telecommunication. For example, when communicating viatelecommunication, a person can adjust, alter, or augment the content oftheir message to an intended recipient through tone, volume, intonation,and cadence. When communicating in-person, or face-to-face, a person canfurther enhance or enrich their spoken words with eye contact and shiftof focus, facial expressions, hand gestures, body language, and thelike. In electronic messaging, users lack these critically importantsignals, clues, and cues, making it difficult for people to convey thesubtler aspects of communication and deeper intent. As a result, issuesof meaning, substance, and sentiment are often lost or confused inelectronic messages, which can, and very often does, result in harmfulor damaging misunderstandings. Miscommunications can be particularlydamaging in interpersonal and business relationships.

Another unintended effect of our overreliance on electroniccommunication is the impairment of emotional and mental health. In arecent article published in the American Journal of Psychiatry, Dr.Jerald Block wrote “technology addiction is now so common that it meritsinclusion in the Diagnostic and Statistical Manual of Mental Disorders,the profession's primary resource to categorize and diagnose mentalillnesses.” He went on to further state that the disorder leads to angerand depression when the tech isn't available, as well as lying, socialisolation and fatigue. Our devices and experiences from said devices(receiving likes, comments and shares on social media) are in essence adrug dealer and drugs, respectively: Having the capability of doling outthe same kind of dopamine hit as a tiny bump of cocaine. In effect,creating the typical addiction/dependency vicious cycle and all of theattendant consequences.

According to psychotherapist, Nancy Colier, author of “The Power ofLife”, “We are spending far too much of our time doing things that don'treally matter to us . . . [and become] disconnected from what reallymatters, from what makes us feel nourished and grounded as humanbeings.” Based on her findings, the average person checks theirsmartphones 150 times per day, or every six minutes. Furthermore, theaverage young adult sends on average 110 texts per day and 46% ofrespondents checked that their devices are something that they couldn'tlive without.

With this kind of digital ubiquity, it is becoming readily apparent thatany solution to the problem involving curtailing or augmenting userbehavior is not a realistic approach. Current approaches espoused byexperts involve any one of, or combination of, the following:Downloading an app (Moment, Alter, etc.) that locks or limits phoneusage upon reaching a pre-specified limit; disabling notifications fromyour phone settings; keeping the blue-hued light of your smartphone awayfrom your place of rest; and even buying and carrying around a dummyphone.

There is a void for a solution that takes into account ubiquitous usageand provides delivery of pro-mental and emotional healthcontent—personalized to the user, much like the way therapeutics havebecome narrowly tailored—to counter all of the digital-mediated illeffects plaguing our society. These effects will only logarithmicallygrow as we transition into the IoT era—where we will be exposed tothousands of internet-enabled objects (each capable of deliveringcontextualized analytics and provisioning) as part of our day-to-dayliving. Finally, there is a void in the market for deliveringhyper-personalized digital-based therapeutics based on ahigher-resolution assessment of an EMS (a more dynamic EMS or dEMS). Adynamic assessment based on a multi-correlate coordinate system (moodmap) that allows users to plot as a single point along at least twocorrelates of behavior—resulting in a push of hyper-personalized digitalcontent with therapeutic value to reinforce or counter the user-mappeddynamic assessment.

There is a void for fast-capture input modality for quick-assessment ofan EMS and/or associated neurotransmitter requiring addressing.Furthermore, there is a void in the art combining this fast-capture fordigital delivery of a design-rich visual asset with short suggestions orrecommendations to address the EMS and/or associated neurotransmitter toachieve an acute psychological response. Finally, there is a void in theart combining this fast-capture for digital delivery of moresubstantive, textual based generalized clinician tips to achieve acuteor longitudinal psychological/behavioral responses.

Moreover, there is a void in the art for a method for delivering anencoded mood or EMS profile of a user to a user device—in at least oneof a logged-on, logged-off, rested, or locked state.

SUMMARY

Disclosed is a method and system for imposing a dynamic sentiment vectorto an electronic message. In one embodiment of the invention, the methodcomprises: receiving a text input comprising message content from anelectronic computing device associated with a user; parsing the messagecontent comprised in the text input for emotionally-charged language;assigning a sentiment value, based on the emotionally-charged language,from a dynamic sentiment value spectrum to the text input; and, based onthe sentiment value, imposing a sentiment vector, corresponding to theassigned sentiment value, to the text input, the imposed sentimentvector rendering a sensory effect on the message content designed toconvey a corresponding sentiment.

In another embodiment of the invention, the method comprises: receivinga text input comprising message content from an electronic computingdevice associated with a user; converting the message content comprisedin the text input received from the electronic computing device intoconverted text in a standardized lexicon; parsing the converted text foremotionally-charged language; generating a sentiment value for the textinput from a dynamic sentiment value spectrum by referencing theemotionally-charged language with a dynamic library ofemotionally-charged language; and, based on the sentiment value,imposing a sentiment vector to the text input, the imposed sentimentvector rendering a sensory effect on the message content designed toconvey a corresponding sentiment.

For example, in one application of the invention, a user can write andsubmit a text message on the user's cellular phone for delivery to theuser's best friend. After receiving the text message, the invention cananalyze the message content of the text message and determine, based onthe verbiage, syntax, and punctuation within the message content, thatthe user is attempting to convey excitement through the text message.The invention can then apply a visual filter of red exclamation pointsor other illustrative, performative, or kinetic attributes to the textmessage, indicating the excitement of the user, before the text messageis delivered to the user's best friend.

In another example of one application of the invention, a user can writeand submit a direct message through a social media application (e.g.,Instagram, Facebook, SnapChat) on the user's mobile phone for deliveryto a second user. After receiving the direct message, the invention canuse a camera built into the user's mobile phone to capture an image ofthe user's face and analyze aspects of the user's face (e.g., curvatureof the lips, motion of the eyes, etc.) to determine the user's mood orexpression. Based on the user's mood or expression, the invention canthen apply a vibration pattern to the direct message before the directmessage is delivered to the second user.

In another object of the invention, sentiment and cues of the usersemotional or mental state is not gleamed by referencing a parsed userinput against a dynamic library of emotionally-charged language togenerate a sentiment value and vector for overlaying the said input.Rather, the emotional and mental state (EMS) of the user is chosen bythe user or determined by the system based on user engagement with theinterface or content. Once the EMS of the user is defined, carefullycurated and efficacious content is delivered to the user to combat thedefined EMS.

In one aspect, a method is provided for delivering a digitaltherapeutic, specific to a user-chosen emotional or mental state (EMS),the method comprising the steps of: recognizing at least one EMSselected by the user from a plurality of EMS, the selected EMSindicating at least one of a feeling, sensation, type of discomfort,mood, mental state, emotional condition, or physical status of the user.Once the EMS is defined, the method then calls for pushing aprimary-level message personalized to the user based on at least onestored message coupled to the selected EMS. Finally, pushing at least asecondary-level message personalized to the user based on athreshold-grade match of the user response to the pushed primary-levelmessage with at least one stored response coupled to a storedprimary-level message, whereby the user and stored response is a measureof at least one of a reaction, compliance, engagement, or interactivitywith the pushed and, or stored primary-level message. The primary andsecondary-level messages may contain at least one of a text, image,sound, video, art asset, suggested action or recommended behavior. Theefficaciousness or therapeutic value of the primary or secondarymessages are validated by at least one—and typically two—independentsources of clinical research or peer-reviewed science, as verified by acredentialed EMS expert.

In another aspect, once the EMS is defined, the method may call forpushing at least a single-level message. The at least single message maycontain at least one of a text, image, sound, video, art asset,suggested action or recommended behavior. Again, the efficaciousness ortherapeutic value of the primary or secondary messages are validated byat least one—and typically two—independent sources of clinical researchor peer-reviewed science, as verified by a credentialed EMS expert.

In yet another aspect, a system is described and claimed for deliveringthe digital content of validated therapeutic efficacy. The system maycomprise an EMS store; at least a primary message prescriber; aprocessor coupled to a memory element with instructions, the processorwhen executing said memory-stored instructions, configure the system tocause: at least one EMS from a plurality of EMS in the EMS store to beselected by the user, said selected EMS indicating at least one of afeeling, sensation, type of discomfort, mood, mental state, emotionalcondition, or physical status of the user; and the at least primarymessage prescriber pushing a primary-level message personalized to theuser based on at least one stored message coupled to the selected EMS.

In yet other aspects, at least a secondary message prescriber isincluded, wherein the at least secondary message prescriber pushes atleast a secondary-level message personalized to the user based on athreshold-grade match of the user response to the pushed primary-levelmessage with at least one stored response coupled to a storedprimary-level message, whereby the user and stored response is a measureof at least one of a reaction, compliance, engagement, or interactivitywith the pushed and, or stored primary-level message.

In both aspects (primary or at least secondary message prescribers), themessages or content may contain at least one of a text, image, sound,video, art asset, suggested action or recommended behavior. Much like inthe method aspects, the therapeutic value of the messages or content arevalidated by at least one—and typically two—independent sources ofclinical research or peer reviewed published science and selected by acredentialed EMS expert.

In one other aspect, a system and method for generating a more dynamicassessment allowing for more hyper-personalized digital content deliveryis provided. Users may plot as a single point on a multi-correlatecoordinate system (mood map), wherein each axis represents a uniquecorrelate of behavior and where a single point is a representation of auser-mapped assessment along at least two correlates of behavior, suchas active/inactive and positive/negative. Other reinforcing orcountering correlates may be provided. Moreover, the mood map may bethree-dimensional to include a third correlate of behavior. Finally, themood map and plotted assessment along the at least two correlates ofbehavior may be system enabled, as opposed to user-plotted. The systemmay capture emotional metrics from at least one of a facial imagecapture, heart/respiration rate, skin conductance, sensor gathered,digital footprint crawled, response to cognitive/physical tasks,engagement to pushed content, etc.

Whether the sentiment or cues are generated by the system or defined bythe user, content is being overlaid or delivered to enhance intonation,heighten digital communication, obviate ambiguity, boost mood, supportself-esteem, inspire wellness, and aid in the longitudinal andnon-interventional care for people in distress or need—leveraging afamiliar and known modality (digital devices). According to the claimedinvention, a whole ecosystem of receiving and delivering modalities areprovided for a host of digital therapeutics. The digital therapeuticofferings—with the aid of Artificial Intelligence (AI), machinelearning, and, or predictive EMS assessment tools—may deliverincreasingly personalized solutions uniquely tailored to aid eachsubscriber. Such non-interventional, anonymous, and device-centricsolutions are far more appropriate to combat the rising ill-effects ofdevice dependency—rather than pharmaceutical dosing, in-patienttreatment, and altering device behavior.

In another aspect, a system and method for delivery of a GCT and/orsocial-based digital content for achieving acute and/or longitudinalpsychological/behavioral responses based on a fast capture of an EMSand/or neurotransmitter.

Moreover, one aspect covers for the delivery of a mood or EMS profile toa user device based on an assessed or determined EMS. This profile is asymbol or color-coded representation displayed on a user device in anydevice-state for the user to fast-capture state of emotion or mood. Inanother aspect, this same visual representation of mood profile can bediscerned to communicate a digital content or media diet. As a result, auser can quick-capture an contemporaneous or historical diet to betterinform future media/content consumption choices.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a graphical representation of one embodiment of the electronicmessaging system.

FIG. 2 is a graphical representation of one embodiment of the electronicmessaging system.

FIGS. 3A and 3B are graphical representations of one embodiment of theelectronic messaging system.

FIGS. 4A, 4B, 4C and 4D are graphical representations of one embodimentof the electronic messaging system.

FIGS. 5A, 5B, and 5C are graphical representations of one embodiment ofthe electronic messaging method.

FIG. 6 is a graphical representation of one embodiment of the electronicmessaging method.

FIGS. 7A and 7B are graphical representations of one embodiment of theelectronic messaging system.

FIGS. 8A, 8B, 8C, and 8D is a graphical representation of one embodimentof the electronic messaging system. are flow diagrams of one embodimentof the electronic messaging system.

FIG. 9 illustrates a network diagram in accordance with an aspect of theinvention.

FIG. 10 illustrates a block diagram depicting the digital therapeuticsystem in accordance with an aspect of the invention.

FIG. 11 illustrates a block diagram depicting the digital therapeuticsystem in accordance with an aspect of the invention.

FIG. 12 illustrates a flow diagram depicting the digital therapeuticmethod in accordance with an aspect of the invention.

FIG. 13 illustrates a representative screen shot depicting an exemplaryuser interface in accordance with an aspect of the invention.

FIG. 14 illustrates a representative screen shot depicting an exemplaryuser interface in accordance with an aspect of the invention.

FIG. 15 illustrates a representative screen shot depicting an exemplaryuser interface in accordance with an aspect of the invention.

FIG. 16 illustrates a representative screen shot depicting an exemplaryuser interface in accordance with an aspect of the invention.

FIG. 17 illustrates a block diagram representing a system including themood mapper module in relation to the EMS store and prescribers inaccordance with an aspect of the invention.

FIG. 18 illustrates a graphical representation of the mood map includingthe at least two correlates of behavior underlying the user-plottedassessment of behavior in accordance with an aspect of the invention.

FIG. 19A, FIG. 19B, FIG. 19C, and FIG. 19D are exemplary screen shots ofthe mood map interface in accordance with an aspect of the invention.

FIG. 20A and FIG. 20B are exemplary screen shots of thehyper-personalized digital therapeutic pushed to the user-plotteddynamic EMS.

FIG. 21 illustrates a method flow chart for generating thehyper-personalized digital therapeutic pushed to the user-plotteddynamic EMS.

FIG. 22 illustrates a method flow chart for delivering an audio-basedcontent (digital therapeutic or digital pharmaceutical) in accordancewith an aspect of the invention.

FIG. 23A is an exemplary system block diagram of the GCT delivery inaccordance with an aspect of the invention.

FIG. 23B is an exemplary method flow chart of the GCT delivery inaccordance with an aspect of the invention.

FIG. 24 is an exemplary method flow diagram detailing the steps indelivering an encoded profile to a user device in accordance with anaspect of the invention.

FIG. 25 is an exemplary encoded profile as displayed on a smartphone/watch in accordance with an aspect of the invention.

FIG. 26 is an exemplary encoded profile as displayed on a smartphone/watch in accordance with an aspect of the invention.

DETAILED DESCRIPTION OF DRAWINGS

Numerous embodiments of the invention will now be described in detailwith reference to the accompanying figures. The following description ofthe embodiments of the invention is not intended to limit the inventionto these embodiments but rather to enable a person skilled in the art tomake and use this invention. Variations, configurations,implementations, and applications described herein are optional and notexclusive to the variations, configurations, implementations, andapplications they describe. The invention described herein can includeany and all permutations of these variations, configurations,implementations, and applications.

In the following description, numerous specific details are set forth inorder to provide a thorough understanding of the invention. It will beapparent, however, to one skilled in the art that the invention can bepracticed without these specific details.

Reference in this specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the invention. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment, nor are separate or alternative embodimentsmutually exclusive of other embodiments. Moreover, various features aredescribed which may be exhibited by some embodiments and not by others.Similarly, various requirements are described which may be requirementsfor some embodiments but no other embodiments.

FIG. 1 depicts a schematic of a system 100 for imposing a dynamicsentiment vector to an electronic message. In one embodiment, a system100 can include: a sentiment vector generator 110, a processor 120, andan electronic computing device 140 associated with a particular user130. The sentiment vector generator 110, the processor 120, and theelectronic computing device 140 are communicatively coupled via acommunication network. The network may be any class of wired or wirelessnetwork including any software, hardware, or computer applications thatcan provide a medium to exchange signals or data. The network may be alocal, regional, or global communication network.

The electronic computing device 140 may be any electronic device capableof sending, receiving, and processing information. Examples of thecomputing device include, but are not limited to, a smartphone, a mobiledevice/phone, a Personal Digital Assistant (PDA), a computer, aworkstation, a notebook, a mainframe computer, a laptop, a tablet, asmart watch, an internet appliance and any equivalent device capable ofprocessing, sending and receiving data. The electronic computing device140 can include any number of sensors or components configured to intakeor gather data from a user of the electronic computing device 140including, but not limited to, a camera, a heart rate monitor, atemperature sensor, an accelerometer, a microphone, and a gyroscope. Theelectronic computing device 140 can also include an input device (e.g.,a touchscreen or a keyboard) through which a user may input text andcommands.

As further described below, the sentiment vector generator 110 isconfigured to receive an electronic message 160 (e.g., a text input)from the particular user 130 associated with the electronic computingdevice 140 and run a program 116 executed by the processor 120 toanalyze contents of the electronic message, determine a tone or asentiment that the particular user 130 is expressing through theelectronic message 160, and apply a sentiment vector to the electronicmessage 160, the sentiment vector designed to convey the tone orsentiment determined by the sentiment vector generator 110. Theelectronic message 160 can be in the form of a SMS message, a textmessage, an e-mail, a social media post, an enterprise-level workflowautomation tool message, or any other form of electronic, text-basedcommunication. The electronic message 160 may also be a transcription ofa voice message generated by the particular user 130. For example, inone embodiment, from a messaging application installed on the electroniccomputing device 140, the user 130 may select to input a voice (i.e.,audio) message through a microphone coupled to the electronic computingdevice 140 or initiate a voice message through a lift-to-talk feature(e.g., the user lifts a mobile phone to the user's ear and the messagingapplication automatically begins recording a voice message). In thisexample, the system 100 can generate a transcription of the voicemessage or receive a transcription of the voice message from themessaging application. After receiving or generating the transcription(i.e., an electronic message), the sentiment vector generator 110 canthen analyze the message content within the electronic message,determine the mood or sentiment of the message content, and apply acorresponding sentiment vector to the electronic message, as furtherdescribed below.

In one embodiment, the system 100 may receive an electronic message 160in the form of an electroencephalograph (EEG) output. For example, inthis embodiment, a user can generate a message using an electronicdevice communicatively coupled to the user and capable of performing anelectroencephalograph to measure and record the electrochemical activityin the user's brain. In this example, the system 100 can transcribe theEEG output into an electronic message 160 or receive a transcription ofthe EEG output from the electronic device communicatively coupled to theuser. After receiving or generating the electronic message 160 from theEEG, the sentiment vector generator 110 can then analyze the messagecontent within the electronic message 160, determine the mood orsentiment of the message content, and apply a corresponding sentimentvector to the electronic message. In one example of this embodiment, auser is connected to an augmented reality (AR) or virtual reality (VR)headset capable of performing an EEG or an equivalent brain mappingtechnique. The user can generate a message simply by thinking of whatthe user is feeling or would like to say. The headset can monitor andrecord these thoughts and feelings using the EEG and transcribe thethoughts and feelings into an electronic message or send the EEG outputsignals directly to the system 100. The system 100 can then analyze themessage content included within the electronic message 160, determinethe mood or sentiment of the message content, and apply a correspondingsentiment vector to the electronic message 160, creating a vectorizedmessage. The system 100 can then send the vectorized message to theuser's intended recipient (e.g., a recipient that the user thought of).

In one embodiment, the particular user 130 may submit an electronicmessage 160 through a mobile application (e.g., a native or destinationapp, or a mobile web application) installed on the particular user'smobile phone or accessed through a web browser installed on the user'sphone. In one example of this embodiment, the user accesses the mobileapplication, submits the electronic message 160 in the form of a textinput. The sentiment vector generator110 can then analyze the messagecontent included within the electronic message 160, determine the moodor sentiment of the message content, and apply a corresponding sentimentvector to the electronic message 160, creating a vectorized message. Inthis example, the user can then send the vectorized message to theuser's intended recipient(s) 131 (e.g., by copying and pasting thevectorized message into a separate messaging application or selecting toexport the vectorized message to a separate application, as furtherdescribed below). In one variation of this embodiment, the user may sendthe vectorized message to the intended recipient 131 directly throughthe mobile application. In one embodiment, the user may submit anelectronic message 160, or a component of an electronic message (e.g., asingle word or phrase within the message content of an electronicmessage) using a touch input gesture. In one example of this embodiment,the user may submit the electronic message 160 through an electroniccomputing device by swiping a finger on a touch screen coupled to theelectronic computing device 140 in a U-shaped gesture on the electronicmessage.

In another embodiment, the user may input an electronic message 160 intoan entry field of a third-party application such as an email client(e.g., Gmail, Yahoo Mail) or a social media application (e.g., Facebook,Twitter, Instagram). For example, the user may input a message into thebody of an email, or into a status update on Facebook. In thisembodiment, the system 100 can detect the input of the electronicmessage 160 into the third-party application and upload the electronicmessage 160 to the sentiment vector generator 110. The sentiment vectorgenerator 110 can then analyze the message content contained within theelectronic message 160, determine the mood or sentiment of the messagecontent, and apply a corresponding sentiment vector to the electronicmessage 160, creating a vectorized message. The sentiment vector 110 canthen replace the electronic message 160 within the third-partyapplication with the vectorized message. Alternatively, the user mayselect to replace the electronic message 160 with the vectorized message(e.g., by copying and pasting the vectorized message into the entryfield).

FIG. 2 depicts a [schematic] of the sentiment vector generator 110. Inone embodiment, the sentiment vector generator 110 includes a parsingmodule 112, a dynamic sentiment value spectrum 114, a program 116, and alibrary of sentiment vectors. In this embodiment, after receiving anelectronic message 160, the sentiment vector generator 110 can activatethe program 116 executed by a processor 120 to analyze message contentcontained within the electronic message 160 using the parsing module112, the sentiment value spectrum 114, and the library of sentimentvectors, which are discussed in further detail below. Part or all of thesentiment vector generator 110 may be housed within the electroniccomputing device 140. Likewise, part of all of the sentiment vectorgenerator 110 may be housed within a cloud computing network.

FIG. 3 depicts a schematic of the parsing module 112. The parsing module112 is configured to parse message content contained within anelectronic message 160 received by the sentiment vector generator 110for emotionally-charged language and determine a sentiment value for theelectronic message 160 from the dynamic sentiment value spectrum 114. Inone embodiment, the parsing module 112 can include one or both of aheuristic layer 112 a and a semantic layer 112 b. The heuristic layer112 a is configured to recognize, within the message content containedwithin the electronic message 160, shorthand script, symbols, andemotional icons (emoticons). For example, the message “r u okay?:(”contains the shorthand character “r” to represent the word “are,” theshorthand character “u” to represent the word “you,” and the emoticon“:(,” representing an unhappy face, each of which the heuristic layer112 a is configured to recognize. The heuristic layer 112 a can befurther configured to translate recognized shorthand script, symbols,and emoticons into a standardized lexicon. For example, referring backto the previous example, the heuristic layer can translate “u” into“you,” “r” into “are,” and “:(” into “[sad].” The heuristic layer 112 acan thus translate the entire message from “r u okay?:(” to “are youokay? [sad]” in order to compare the sentiments expressed withindifferent messages in a more objective manner and determine the natureof the emotionally-charged language contained within the message ofcontent of the electronic message 160.

The semantic layer 112 b is configured to recognize, within the messagecontent contained within the electronic message 160, natural languagesyntax. For example, in the message “is it ok if we text on WhatsApp?”the construction of the phrases “is it ok” and “WhatsApp?” reflectnatural language syntax that can express particular sentiments. “is itok[?]” can express tentativeness in addition to the objective questionthat the phrase asks. For reference, inverting and contracting the firsttwo words to create the phrase “it's okay[?]” results in a phrase thatcan express more confidence. Likewise, the space inserted between“WhatsApp” and “?” can have the effect of “softening” the question markin comparison to “WhatsApp?” The semantic layer 112 b is configured torecognize the use of natural language syntax such as “is it ok” and“WhatsApp?” and can be further configured to translate the recognizednatural language syntax into a standardized lexicon. The standardizedlexicon can be a standard set of words and terms (e.g., an Oxforddictionary) that the parsing module 112 is able to parse foremotionally-charged language. In one embodiment, the standardizedlexicon is a standard set of words and terms with predefined attributes.For example, again referring to the previous example, the semantic layer112 b can translate the entire message from “is it ok if we text onWhatsApp?” to “can[soft] we text on WhatsApp?[soft]” in order to comparethe sentiments expressed within different messages in a more objectivemanner and determine the nature of the emotionally-charged languagecontained within the message of content of the electronic message 160.

In one embodiment, the parsing module 112 can include a library ofemotionally-charged language 112 c. In this embodiment, after parsingthe message content contained within the electronic message 160, theparsing module 112 can cross-reference the words and terms containedwith the message content to the library of emotionally-charged language112 c. The words and terms contained within the library ofemotionally-charged language 112 c may be tagged with attributesaccording to the sentiments they most commonly express. For example, thelibrary of emotionally-charged language 112 c may include the terms“disastrous,” “splendid,” “terrible,” and “awesome.” Within the libraryof emotionally-charged language 112 c, “disastrous” may be tagged withthe attribute [bad] or [negative]; “splendid” may be tagged with theattribute [good] or [positive]. In one embodiment, the terms containedwithin the library of emotionally-charged language 112 c mayadditionally or alternatively be tagged with a numeric value. Forexample, “disastrous” may be tagged with the attributes [negative; 7],and “terrible” may be tagged with the attributes [negative; 5],indicating that while “disastrous” and “terrible” may express similar“negative” sentiments, “disastrous” is more negative than “terrible.” Inone embodiment, the parsing module 112 (or, alternatively, any componentof the system 100) can dynamically add or remove words or terms to andfrom the library of emotionally-charged language 112 c. The parsingmodule 112 may use any technique to tag or evaluate the sentiments ofemotionally-charged language.

In one embodiment, the library of emotionally-charged language 112 c isspecific to the particular user 130. In this embodiment, each particularuser 130 of the system 100 access a unique library ofemotionally-charged language 112 c associated only with that particularuser. In one variation of this embodiment, the particular user 130 maymanually add or remove words and terms to and from the library ofemotionally-charged language 112 c. In one embodiment of the system 100,the system 100 can be accessed by multiple users. In one variation ofthis embodiment, the library of emotionally-charged language 112 cemployed by the parsing module 112 is the same for each user.

In one embodiment of the system 100, the parsing module additionallyincludes a neural network 150 and a library of inputs 151. In thisembodiment, after parsing the message content of an electronic message160 received by the sentiment vector generator 11, the parsing module112 can store the electronic message 160 in the library of inputs 151,along with the emotionally-charged language found within the messagecontent and any accompanying attributes, creating a database of messagesand their accompanying emotionally-charged language. In this embodiment,the neural network 150 can employ machine learning techniques to analyzethis database for patterns and trends in order to dynamically improvethe performance of the sentiment vector generator 110. For example, theneural network 150 may determine through the application of an algorithmthat the particular user 130 uses the term “disastrous” ten times moreoften than the particular user 130 uses the term “terrible.” Thus, eventhough “disastrous” may be a more negative term than “terrible” for theaverage user or person, the neural network can determine that, for theparticular user 130, “disastrous” generally carries less emotionalweight than “terrible.” In this example, the neural network 150 can thenupdate the parsing module 112 and the library of emotionally-chargedlanguage accordingly. For example, in the example in which the terms“disastrous” and “terrible” begin as tagged within the library ofemotionally-charged language 112 c as [negative; 7] and [negative; 5],respectively, the neural network 150 can update the attributes to read[negative; 5] and [negative 7], respectively. In one embodiment, theparsing module 112 can store electronic messages into the library ofinputs 151 along with their standardized lexicon conversions.

FIG. 4 depicts graphical representations of the parsing of electronicmessages by the parsing module 112. FIG. 4A depicts the parsing of threeseparate electronic messages 160, “it definitely has given me more timeand flexibility and channels creativity differently” 160 a, “is it ok ifwe text on WhatsApp?” 160 b, and “Oh u live in Williamsburg” 160 c foremotionally-charged language by the parsing module 112. In, thisexample, in the message content of 160 a, the parsing module 112determines three emotionally-charged words and terms: “definitely has,”“and,” and “differently;” in the message content of 160 b: “ok,” “we,”and “WhatsApp?” and in the message content of 160 c: “u” and“Williamsburg.” In one embodiment, as discussed above, after parsing themessage content, the parsing module 112 can determine attributes for theemotionally-charged language found in the message content, as depictedby S123 in FIG. 4B. In the example depicted in FIG. 4B, the parsingmodule 112 tags “definitely has” with [positive, active], “and” with[neutral], and “differently” with [negative]. In one embodiment, asdiscussed above, the parsing module 112 includes a semantic layer 112 bconfigured to recognize, within the message content contained within theelectronic message 160, natural language syntax, as depicted by S122 inFIG. 4B. In the example depicted in FIG. 4B, the semantic layer 112 brecognizes the space between “WhatsApp” and “?” in “is it ok if we texton WhatsApp?” as an instance of natural language syntax. In oneembodiment, as discussed above, the parsing module 112 includes aheuristic layer 112 a configured to recognize, within the messagecontent contained within the electronic message 160, shorthand script,symbols, and emoticons, as depicted by S124 in FIG. 4B. In the exampledepicted in FIG. 4B, the heuristic layer 112 a recognizes “u” as ashorthand term for “you.”

In one embodiment, as discussed above, after parsing the message contentcontained within the electronic message 160, the parsing module 112 cancross-reference the words and terms contained with the message contentto a library of emotionally-charged language 112 c, as depicted in FIG.4C. In the example depicted in FIG. 4C, the parsing module 112cross-references electronic message 160 a with the library ofemotionally-charged language 112 c and determines that “differently,”“more,” “flexibility,” and “differently” are emotionally-charged wordsor terms. In one embodiment, as discussed above, before parsing themessage content of an electronic message 160, the parsing module 112 canconvert the message content into a standardized lexicon, as depicted inFIG. 4D. In the example depicted in FIG. 4D, the parsing module 112converts “is it ok if we text on WhatsApp?” into the converted text, “isit okay if we text on WhatsApp?” in step S126 before parsing theconverted text for emotionally-charged language in step S128.

FIGS. 5A, 5B, and 5C depict a graphical representation of a dynamicsentiment value spectrum 114. In one embodiment, after parsing messagecontent of an electronic message 160 for emotionally-charged language,the sentiment vector generator 110 can generate a sentiment value from adynamic sentiment value spectrum 114 for the electronic message 160. Inone variation of this embodiment, the dynamic sentiment value spectrum114 can be represented as a coordinate system, as depicted in FIG. 5A.In the example depicted in FIG. 5A, the dynamic sentiment value spectrum114 is a Cartesian coordinate system consisting of two axes: ahorizontal axis 115 a ranging from positive to negative (henceforth, thepositivity axis) and a vertical axis 115 b ranging from passive toactive (henceforth, the activity axis). In this example, the dynamicsentiment value spectrum 114 consists of a multitude of differentsentiments, each occupying a different position on the coordinatesystem. For example, the sentiments “Happy,” “Astonished,” and“Inquisitive” (114 a-114 c, respectively) all occupy the second quadrantof the coordinate system, defined by a positive position on thepositivity scale and an active position on the activity scale (i.e.,each of these sentiments are determined by the sentiment vectorgenerator 110 to be positive and active sentiments). In this example,the sentiment vector generator considers Inquisitive 114 c to be a moreactive but less positive sentiment than Astonished 114 b and Astonishedto be a less positive and less active sentiment than Happy 114 a. Also,in this example, the sentiments “Shocked,” “Sad,” and “Mad” (114 d-114f, respectively) all occupy the first quadrant of the coordinate system,defined by a negative position on the positivity scale and an activeposition on the activity scale (i.e., each of these sentiments aredetermined by the sentiment vector generator to be active and negativesentiments). However, the dynamic sentiment value spectrum 114 need notbe a coordinate system. Rather, the dynamic sentiment value spectrum 114may take on any appropriate form (e.g., a list, a linear scale, etc.).Additionally, the sentiment value spectrum does not need to be dynamic.

In one embodiment, as discussed above, after parsing message contentcontained within an electronic message 160 for emotionally-chargedlanguage, the parsing module 112 can assign attributes to theemotionally-charged language found in the message content of theelectronic message 160. In one embodiment, the sentiment vectorgenerator 110 can analyze the emotionally-language and theiraccompanying attributes to generate a sentiment value from the dynamicsentiment value spectrum 114, as depicted in FIG. 5B. For example, inthe example depicted in FIG. 5B, the parsing module 112 can assign eachemotionally-charged term found in the message content of an electronicmessage with respective coordinate values on the positivity and activityaxes of the Cartesian coordinate dynamic sentiment value spectrumdiscussed in the example above. In this example, the sentiment vectorgenerator 110 can take the coordinate position of eachemotionally-charged term, calculate an average position of theemotionally-charged terms, and plot the average positon on the dynamicsentiment value spectrum 114 depicted in FIG. 5A. Then, in this example,the sentiment vector generator 110 can generate a sentiment value forthe electronic message by determining the sentiment value on the dynamicsentiment value spectrum 114 closest to the average position of theemotionally-charged terms.

In one embodiment, the sentiment vector generator 110 can generate asentiment value for an electronic message 160 by determining which ofthe emotionally-charged terms found in the message content of theelectronic message carries the most emotional weight. For example, inone embodiment, the parsing module 112 can parse the message content ofan electronic message 160 for emotionally-charged language and assigneach emotionally- charged term with a positivity scale value, anactivity scale value, and an emotional weight value. In this embodiment,the sentiment vector generator 110 can then determine a sentiment valuefor the electronic message by determining which of theemotionally-charged terms has the highest emotional weight value, andthen determining the sentiment value on the dynamic sentiment valuespectrum 114 closest to the position of emotionally-charged term withthe highest emotional weight value.

In one embodiment, the library of emotionally-charged language 112 cassociates each emotionally-charged term contained within the librarywith a sentiment value from the dynamic sentiment value spectrum 114.For example, the library of emotionally-charged language 112 c mayassociate the words “gleeful,” “splendid,” and “terrific” with a “happy”sentiment value. In this example, if the message content of anelectronic message 160 includes any of the terms “gleeful,” “splendid,”or “terrific,” the sentiment vector generator 110 can generate a “happy”sentiment value for the electronic message 160. However, the sentimentvector generator can generate a sentiment value for an electronicmessage 160 using any other methodology.

In one embodiment, the particular user 130 may select a sentiment valuefrom the dynamic sentiment value spectrum for an electronic message 160.In one variation of this embodiment, after the parsing module 112 parsesthe message content of an electronic message 160 submitted by theparticular user 130, the sentiment vector generator 110 can generatemultiple sentiment values for the electronic message 160 and present themultiple sentiment values for the electronic message 160 to theparticular user 130 for selection. For example, after receivingelectronic message 160 a (depicted in FIG. 4A), the sentiment vectorgenerator 110 may generate an “excited” sentiment value and a“melancholy” sentiment value for electronic message 160 a. In thisexample, the particular user 130 may be given the choice to pick betweenthe “excited” sentiment value and the “melancholy” sentiment value, inorder to further ensure that the proper (i.e., intended) sentiment willbe expressed.

In one embodiment, as discussed above, the system 100 includes a neuralnetwork 150 and a library of inputs 151 communicatively coupled to thesentiment vector generator 110.In one variation of this embodiment,after generating a sentiment value for an electronic message 160, thesentiment vector generator 110 store the electronic message 160 and itsaccompanying sentiment value in the library of inputs 151 creating adatabase of messages and their accompanying sentiment values. In thisembodiment, the neural network 150 can employ machine learningtechniques to analyze this database for patterns and trends in order todynamically improve the performance of the sentiment vector generator110. In one variation of this embodiment, the neural network 150 candynamically edit or rearrange the dynamic sentiment value spectrum 114.In the rearranged version, the sentiment values have adjusted andcoalesced into more discrete sections (115 c-115 e). This may reflectthat a particular user 130 associated with the rearranged sentimentvalue spectrum 117 generates messages most of their messages with asimilar tone, making the difference between similar sentiments subtlerthan that of the average person.

In one embodiment, the sentiment vector generator 110 can generate asentiment value for an electronic message 160 at least in part byutilizing information about a particular user 130. For example, in oneembodiment, the system 100 can generate sender context associated with aparticular user 130. The sender context can include, but is not limitedto: social media data associated with the particular user, data obtainedfrom IoT (internet of things) devices associated with the particularuser, data obtained from wearable devices associated with the particularuser, genetic profile data associated with the particular user, andstress data of the particular user. In one variation of this embodiment,the system 100 can leverage sensors and inputs coupled to an electroniccomputing device 140 associated with the particular user 130 to generatesender context associated with the particular user 130, as depicted bystep S160 in FIG. 6. For example, in the example depicted in FIG. 6, thesystem 100 can leverage a camera built into a mobile phone associatedwith the particular user 130 to capture images of the face of theparticular user. In this example, the system 100 can then analyze theimages of the face of the user (e.g., the eye motion or lip curvature ofthe user) and determine the mood of the user at the time that theelectronic message 160 is generated. The sentiment vector generator 110can then generate a sentiment value using the determined mood of theuser. In one variation of this embodiment, the system 100 can leveragesensors coupled to wearable devices associated with a particular user,such as a smart watch, intelligent contact lenses, or cochlear implants.For example, the system 100 can leverage a microphone built into acochlear implant to capture the heartrate of a user at the time that theuser is generating an electronic message 160. Using the capturedheartrate, the sentiment vector generator 110 can then determine astress level of the user at the time that the user generated theelectronic message 160 and generate a sentiment value using thedetermined stress level of the user. Sender context can additionally oralternatively include: facial expression, motion or gesture, respirationrate, heart rate, and cortisol level.

In another variation of the previous embodiment, the sentiment vectorgenerator 110 can generate a sentiment value for an electronic message160 at least in part by utilizing information about an intendedrecipient of the electronic message 160. In this embodiment, afterreceiving an electronic message 160, the system 100 can determine anintended recipient 131 of the electronic message 160. The system 100 canthen generate recipient context associated with the intended recipient131. The recipient context can include but is not limited to: socialmedia data associated with the intended recipient, data obtained fromIoT (internet of things, e.g., a smart home assistant such the AmazonEcho) devices associated with the intended recipient, data obtained fromwearable devices associated with the intended recipient, genetic profiledata associated with the intended recipient, and stress data associatedwith the intended recipient. For example, in one embodiment, the system100 can leverage sensors built into an electronic device 141 associatedwith the intended recipient to determine a mood of the intendedrecipient 131 at the time that the electronic message 160 is generated.The sentiment vector generator 110 can then generate a sentiment valuefor the electronic message 160 based at least in part on the determinedmood of the intended recipient 131.

After generating a sentiment value for an electronic message 160, thesentiment vector generator 110 can then select a sentiment vector from alibrary of sentiment vectors 118, the selected sentiment vector designedto convey a sentiment corresponding to the generated sentiment value,and impose the selected sentiment vector to the electronic message 160,as depicted in FIG. 7. The library of sentiment vectors 118 can includebut is not limited to: a color change of a component of the messagecontent, a change in the text font of a component of the messagecontent, an audio effect, a haptic effect, and a graphical addition tothe message content. For example, in one embodiment, after generating a“mad” sentiment value, the sentiment vector generator 110 may change thebackground of the electronic message 160, as depicted by step S141 a inFIG. 7A, such as changing the background of the electronic message 160to red to reflect the mad sentiment. Or, for example, in one variationof this embodiment, the sentiment vector generator 110 may opt tohighlight only key words or terms in red, or change the fonts of keywords or terms to red. The sentiment vector generator 110 can impose anysort of color change to the electronic message 160 in order to convey acorresponding sentiment.

In one embodiment, for example, after generating an “inquisitive”sentiment value for an electronic message 160, the sentiment vectorgenerator 110 may impose a graphic onto the electronic message 160, asdepicted by step 141 b in FIG. 7A, such as adding question mark graphicsto the background of the electronic message 160. In one variation ofthis example, the sentiment vector generator 110 can add one questionmark to the end of the message content of the electronic message 160 ina font size that is larger than the font size of the rest of the messagecontent. In another variation of this example, the sentiment vectorgenerator 110 may impose a .gif file to the background of electronicmessage 160, in which one question mark grows and shrinks in periodicintervals. The sentiment vector generator 110 can impose any sort ofstatic or dynamic graphic to the electronic message 160 in order toconvey a corresponding sentiment.

In one embodiment, for another example, after generating a “judgmental”sentiment value for an electronic message 160, the sentiment vectorgenerator 110 can edit the font of a key word in the message content, asdepicted by step S141 c in FIG. 7A, such as italicizing one of the wordscontained in the message content. Such font effects can include, but arenot limited to, italicizing the font, changing the size of the font,bolding, underlining, and changing the spacing between characters,words, and lines. The sentiment vector generator 110 can impose any sortof font change to the electronic message 160 in order to convey acorresponding sentiment.

In one embodiment, the sentiment vector generator 110 can impose ananimated character or personality to the electronic message 160, ortranspose the electronic message 160 into a graphic of an animatedcharacter or personality. For example, in one variation of thisembodiment, the library of sentiment vectors 118 may include a series ofthe same animated character (take, for example, an animated llama orchicken) performing various actions associated with variouscorresponding sentiments. For example, the library of sentiment vectors118 may include a static or dynamic graphic of an animated chickenstomping with red eyes (expressing anger), another graphic of theanimated chicken laying in a hammock and basking in the sun (expressingcontentedness), and another graphic of the animated chicken blowing akiss (expressing affection). In this example, after generating an“anger” sentiment value for an electronic message 160, the sentimentvector generator 110 can transpose the electronic message into thegraphic of the animated chicken stomping and saying the message contentof the electronic message 160.

In one embodiment, the sentiment vector generator 110 can impose ahaptic effect onto an electronic message 160. For example, aftergenerating an “anger” sentiment value for an electronic message 160, thesentiment vector generator 110 can impose a vibration or vibrationpattern onto the electronic message 160, as depicted by step S141 d inFIG. 7B, such as three short vibrations. In another example, aftergenerating a “contented” sentiment value for an electronic message 160,the sentiment vector generator 110 can impose one long and mutedvibration to the electronic message 160. The sentiment vector generator110 can impose any form of vibration or vibration pattern to anelectronic message in order to convey a corresponding sentiment.

In one embodiment, the sentiment vector generator 110 can impose anaudio effect onto an electronic message 160. For example, aftergenerating an “unhappy” sentiment value for an electronic message 160,the sentiment vector generator 110 can impose an audio accompanimentonto the electronic message 160, as depicted by step S142 in FIG. 7B,such as protracted “nooo.” In another example, the sentiment vectorgenerator 110 can impose a voice accompaniment dictating the messagecontent of the electronic message 160 and stressing key words containedwithin the message content. The voice accompaniment may stress key wordscontained within the message content in any number of ways including,but not limited to: increasing or decreasing in volume, changing theintonation of the voice, changing the speed of the voice, or changingthe cadence of the voice accompaniment. In one embodiment, the voiceaccompaniment vector may be a recorded and processed version of theparticular user's voice. In one embodiment, the voice accompanimentvector may be the voice of another individual, such as a celebrity, or acombination of the particular user's voice and the voice of anotherindividual.

In one embodiment, after generating a sentiment value for an electronicmessage 160, the sentiment vector generator 110 can impose a vector ontothe electronic message 160 that adjusts the position of the wordscontained with the message content of the electronic message, asdepicted by step S141 e in FIG. 7B. In one variation of this embodiment,the adjustment of the words contained within the message content isstatic, such that the words occupy new positions in a static image. Inone variation of this embodiment, the adjustment of the words containedwithin the message content is dynamic, such that the words containedwithin the message content move within the resulting vectorized message.

In one embodiment, a user may submit sentiment vectors to the sentimentvector generator 110. For example, in one embodiment, a user may submita picture or graphic design to impose onto the background of anelectronic message and select a sentiment value for the picture orgraphic design to be associated with. In this example, after generatinga sentiment value for an electronic message 160 corresponding to thesentiment value that the user has selected to associate with the pictureor graphic design, the sentiment vector generator 110 can impose thepicture or graphic design to the background of the electronic message160 to convey the corresponding sentiment. In another example, in onevariation of this embodiment, a user can select a sentiment vectorpreviously included in the library of sentiment vectors 118 andpreviously associated with a sentiment value and disassociate thesentiment vector from the associated sentiment value, or re-associatethe sentiment vector with a different sentiment value. In yet anotherexample, in one variation of this embodiment, a user can select one ormore elements from existing sentiment vectors contained within thelibrary of sentiment vectors 118 and combine them to create a newsentiment vector. In this example, the user can also choose a sentimentvalue to associate with the new sentiment vector. In another example, inone variation of this embodiment, a user can select a sentiment vectorby scrolling through a list of sentiment vectors (e.g., a list includingoptions to adjust text weight, height, font, color, highlight, orcontent animation) using a flicking gesture, within a mobileapplication, on a touch screen coupled to an electronic computingdevice.

The sentiment vector generator can include or generate, but is notlimited to, sentiment vectors using any combination of the elements ofthe sentiment vectors described herein. Additionally, environmentalconditions and factors for example, but not limited to, wind, heat,humidity, cold may also play a role in generating the sentiment vector.

In one embodiment of the system 100, a user can submit an electronicmessage160 to the sentiment vector generator 110 through a mobileapplication (e.g., a native application), as discussed above. In onevariation of this embodiment, the mobile application can storevectorized messages generated by the sentiment vector generator andallow the user to search through the vectorized messages. In thisembodiment, the user can search through the vectorized messages usingdifferent filters or queries including, but not limited to: mood, color,content, and sentiment. For example, in one embodiment, the user canenter a sentiment as “anger” as a search query, and a graphical userinterface of the mobile application can display a list of all of thevectorized messages that the user has created through the sentimentvector generator 110 with a sentiment value corresponding to an “anger”sentiment. In one embodiment, the sentiment vector generator 110 canimpose a hyperlink onto an electronic message 160. FIGS. 8A, 8B, 8C, and8D are flow diagrams of one embodiment of the electronic messagingsystem.

In an embodiment of the invention, the sentiment vector generator 110can impose a hyperlink onto an electronic message 160. An imperativefunction of the sentiment vector is GEEQ (genetics, emotion andelectroencephalography) and its capacity to integrate messages andmessaging with movement and thought as well as the ability to pairinformation with form and performative elements. In a nutshell, ourtechnology will introduce, integrate, account for, and actively utilizeGEEQ (Genetics, Emotion, and Electroencephalography). GEEQ, by its verydesgn, integrates and intermingles the beliefs and postulates of Darwin,Mendel, Mendelssohn, Morgan, and Martha Graham.

FIG. 9 illustrates a network diagram of the digital therapeutic systemin accordance with an aspect of the invention. As shown, at least oneprocessor 204 is connected to the Internet (network) 206 via either awireless (e.g. WiFi link) or wired link to an Internet connected router,usually via firewall. The network 206 may be any class of wired orwireless network including any software, hardware, or computerapplications that can provide a medium to exchange signals or data. Thenetwork 206 may be a local, regional, or global communication network.Various servers 204, such as a remote VCS Internet server, andassociated database memory can connect with the at least a user device(1 . . . n). Additionally, various user devices (e.g. Smartphones,tablet computers, laptop computers, desktop computers and the like) canalso connect to both the processor-controlled IoT hubs, sensors disposedon the device configured for data gathering, and/or the remote VCSInternet server 204.

As will be discussed, often a plurality of different user devices may beused, but for simplicity this plurality of devices will often be spokenof in the singular form. This use of the singular form is not intendedto be limiting, and in general the claims and invention should beunderstood as operating with a plurality of devices. Although forsimplicity, often mobile client computerized devices such as Internetconnected versions of the popular Android, iOS, or Windows smartphonesand tablets will be used as specific examples of devices, these specificexamples are not intended to be limiting. The electronic computingdevice may include any number of sensors or components configured tointake or gather data from a user of the electronic computing deviceincluding, but not limited to, a camera, a heart rate monitor, atemperature sensor, an accelerometer, a microphone, and a gyroscope. Theelectronic computing device can also include an input device (e.g., atouchscreen or a keyboard) through which a user may input text andcommands.

While not shown, note that server, Internet connected storage device anddatabase memory may all be located in the cloud. This is intended toboth designate and remind the reader that the server, Internet connectedstorage device and database memory are in fact operating according toscalable Internet cloud-based methods that in turn operate according toautomated service provisioning and automated virtual machine migrationmethods. As previously discussed, examples of such scalable methodsinclude, but are not limited to, Amazon EC2, Microsoft Windows Azureplatform, and the Google App Engine. Thus, for example, server andInternet connected storage device will often be implemented asautomatically provisioned virtual machines under a cloud service systemthat can create a greater or lesser number of copies of server andInternet connected video storage device and associated database memoryaccording to the underlying demands on the system at any given time.

Preferred embodiments may include the addition of a remote server 204 orcloud server to further provide for back-end functionality and support.Any one of the storage or processing may be done on-board the device orbe situated adjacent or remotely from the system and connected to eachsystem via a communication network 206. In one embodiment, the server204 may be used to support user behavior profiling; user historyfunction; predictive learning/analytics; alert function; network sharingfunction; digital footprint tracking, etc. The remote server 204 may befurther configured to authenticate the user and retrieve data of theuser, device, and, or network and applies the data against a library ofmessages, content, validated user information, etc.

Now in reference to FIGS. 10 and 11. FIGS. 10 and 11 both illustrate anexemplary embodiment of the digital therapeutic delivery system. FIGS.10 and 11 illustrate an exemplary processing unit with at least a oneprescriber 305, 307 configured for displaying interactively therapeuticcontent from an EMS store 303, 403 based on a user-specific EMS. Asshown, the system may comprise an EMS store 303, 403; at least a primarymessage prescriber 305; a processor coupled to a memory element withinstructions, the processor when executing said memory-storedinstructions, configure the system to cause: at least one EMS from aplurality of EMS in the EMS store 303, 403 to be selected by the user.

As shown in FIG. 11, any number of EMS or EMS types may be included inthe EMS store 303, 403. Each EMS may indicate at least one of a feeling,sensation, type of discomfort, mood, mental state, emotional condition,physical status of the user, and, or a behavioral intervention ortraining regimen. FIG. 11 also illustrates the fact that any number ofmessages or interactively therapeutic content may be associated witheach EMS type. Each message; or interactively therapeutic content; orpushed therapeutic may contain at least one of a text, image, sound,video, art asset, suggested action or recommended behavior. The matchingof message; interactively therapeutic content; or pushed therapeuticwith EMS type may be pre-defined by at least one of an accredited expertor source; probabilistic; or deep learned. In a preferred embodiment, anaccredited expert or source will require at least two independentsources of peer-reviewed scholarship or data in order to validate thematch.

The at least primary message prescriber 305 may push a message orinteractively therapeutic content personalized to the user based on atleast one stored message matched to the selected EMS. For example,within the EMS store 403, if EMS 1 (lethargic) is selected as defined bythe user or the system, any one of message 1, 2 . . . n may be selectedby the prescriber 305. The pre-defined messages validated by theaccredited expert may all be messages with documented utility inelevating mood and energy (rubric). The mood and energy documented foreach message may be on a scale. For instance, EMS 1 message 1 may below-moderate; EMS 1/message 2 may be moderate; and EMS 1/message n maybe high-severe, etc. Any variant of the scale may be featured withoutdeparting from the scope of the invention. In other embodiments, themessages, while falling under the same rubric and un-scaled, can varyalong design cues. For instance, the prescriber 305 may choose EMS1/message 2, over other available messages, due to the fact that themessage is comprised of traditionally feminine cues (pink-coloredbauhaus typeface) for a female user. Other user profile or demographicinformation may further inform the prescribers 305 choice of messagetype, such as age, education level, voting preference, etc. User profileor demographic information may be user inputted or digitally crawled.

Still in reference to FIG. 11, the prescriber's 305 choice of messagetype is not specific to a user, user profile, or crawled user data. In acertain embodiment, the prescriber 305 may have to choose between anyone of the message types (message 1, message 2 . . . message n) from theselected EMS type. This type of message assignment may be completelyarbitrary. In other embodiments, the message assignment may be notspecific to a user-generated or crawled profile but may be based on userhistory. In other words, a user's tracked level of engagement with aprevious message or message from a previous session may inform messageassignment by the prescriber 305. Tracking engagement of a user with apushed or prescribed therapeutic message may be by camera-captured eyegazing, touch-screen interaction, time span between pushed therapeuticand user follow-up action, choice of follow-up action, etc.

In some embodiments, the full list of message types is not grouped byEMS type or along any design categories, but rather simply listedarbitrarily and mapped or matched to an appropriate EMS type. In thisarbitrarily listed manner, the prescriber 305 may match to more than oneEMS type. Likewise, a user may be defined by more than one EMS type andbe prescribed the same message type.

FIG. 12 illustrates a flow diagram depicting the method of delivering adigital therapeutic in accordance with an aspect of the invention. In apreferred embodiment, the method may comprise the steps of: (1)recognizing at least one EMS selected by the user from a plurality ofEMS, the selected EMS indicating at least one of a feeling, sensation,type of discomfort, mood, mental state, emotional condition, or physicalstatus of the user 508. Once the EMS is defined, the method then callsfor (2) pushing at least a primary-level message personalized to theuser based on at least one stored message coupled to the selected EMS509.

In some embodiments, the system or method may call for pushing at leasta secondary-level message personalized to the user based on athreshold-grade match of the user response to the pushed primary-levelmessage with at least one stored response coupled to a storedprimary-level message, whereby the user and stored response is a measureof at least one of a reaction, compliance, engagement, or interactivitywith the pushed and, or stored primary-level message. Much like theprimary message or primary-level message, the secondary-level messagesmay also contain at least one of a text, image, sound, video, art asset,suggested action or recommended behavior. Again, the efficaciousness ortherapeutic value of the primary or secondary messages are validated byat least one—and typically two—independent sources of clinical researchor peer-reviewed science, as verified by a credentialed EMS expert.

In order to facilitate the at least secondary message or secondary-levelmessage, the primary prescriber 305 may be used: Assigning a secondmessage to the same user in the same session for the first defined EMStype. As is with the the assignment of the first message, the assignmentof the second may arbitrarily choose among EMS-grouped messages or fromthe full arbitrary list of messages in the EMS store. Moreover, theprimary prescriber 305 may perform the secondary assignment in alogic-defined manner, wherein gathered, contextualized, or profiled datainforms the assignment. In yet other aspects, second-level assignmentmay be performed by at least a secondary message prescriber 307, whereinthe at least secondary message prescriber 307 pushes at least asecondary-level message personalized to the user based on athreshold-grade match of the user response to the pushed primary-levelmessage with at least one stored response coupled to a storedprimary-level message, whereby the user and stored response is a measureof at least one of a reaction, compliance, engagement, or interactivitywith the pushed and, or stored primary-level message.

For instance, when a user-generated or system-generated EMS is definedas ‘unfulfilled’ for user A, a primary prescriber 305 assigns message 2(uplifting; inspiring message) from EMS 1 (unfulfilled). In oneembodiment, a secondary prescriber 307 prescribes a pro-social behavior,such as a local community service, immediately upon a touch interactionwith the first inspiring message pushed. In other embodiments, a levelof engagement, interaction or compliance may be tracked by the system toinfer severity of the EMS. For instance, if user A does not comply withthe touch-interaction requests from the first inspiring message orpro-social behavior recommendation of the second message, then thesecondary prescriber 307 may push a less physically strenuous pro-socialrecommendation, such as suggesting to call an in-network licensed expertor simply make a cash donation to a charitable organization of the userschoosing via a linked micro-payment method. For the purposes ofinferring severity of EMS, any number of diagnostics that leverage anyone of the on-device tools may be used, such as gyroscopic sensors orcameras. Secondary assignment may also be based on learned history, suchas a past positive reaction (compliance) to a receiving a message from aloved one that a donation was made in user A's name to a charitableorganization. Based on such history, a secondary prescriber 307 mayassign a primary or secondary message recommending to make a donation inthe name of a loved one during an ‘unfulfilled’ EMS experienced by userA.

The processing unit may further be communicatively coupled to at leastone of an interface module, display module, input module, logic module,a context module, timeline module, tracking module, notification module,and a payment/gifting module. In accordance with one aspect, thenotification module may be configured to generate reports at regularintervals (such as daily at 12:00 PM, weekly and monthly), on-demand(when the user requests for a report corresponding to the user), whentriggered by an event, or upon a detected severe EMS. In an embodimentof the present invention, the notification module may also be configuredto send a notification to the user or to a chosen loved one of the user.The notification may be a message, a phone call or any othercommunication means.

In an embodiment of the present invention, a timeline module may pushalready pushed messages in at least one of a static, dynamic, and, orscheduled fashion based on at least one of the user's schedulercriteria. The line of static, dynamic, and, or scheduled messages may becurated by the user, pre-set, or dynamically pushed based on any one ofa user parameter. In some embodiments, the timeline module enables thedisplayed line of static, dynamic, and, or scheduled messages to befurther replicated on at least one of a social media timelines orstories. In other words, the timeline module enables the displayedmessages to be further shared with social media outlets.

In an embodiment of the present invention, a payment or gifting modulemay enable purchasing and gifting donations, physical objects, ordigital assets. The gifting module may further be coupled to adistributive digital ledger, wherein each transaction among any user isrepresented as a unique node in the digital ledger. Each node taggedwith meta data facilitating at least one of a transaction, validationand, or registration for each transaction.

FIG. 13 is a representative screen shot depicting an exemplary userinterface in accordance with an aspect of the invention. As shown, thetop layer 602 depicts a spotlighted EMS and the bottom layer is a scrollmenu of EMS. In this case, the concept of EMS, as earlier defined, alsoincludes behavioral interventions or training regimens, in addition toan emotional and mental state. In some embodiments, an exemplary userexperience may have both top layer 602 and bottom layer 604 within thesame screen, wherein the top layer 602 is a spotlighted rendering of thefocused EMS from the EMS menu depicted in the bottom layer 604. In otherembodiments, the window may only feature the scrolling EMS menu asdepicted in the bottom layer 604, wherein the focused EMS from theplurality of EMS may pop-out, or be emphasized anyhow. In yet otherembodiments, the window may only feature the one EMS at a time, allowingfor the user to go through the entire menu, one window (EMS) at a time.In yet other embodiments, the menu may be featured in a thumbnailformat, allowing the user to choose at least one EMS from a thumbnailmenu, sized to fit in a single window, or alternatively, configured forscrolling.

FIG. 14 is a representative screen shot depicting an exemplary userinterface in accordance with an aspect of the invention. Once the EMS(behavioral intervention or training regimen) is defined, users can readmore about the intervention or training regimen they're going to startand self-administer (have pushed to their device) from a top portion ofthe card (window) 702. On the same card (window), the bottom portion mayhighlight proven benefits, and then provide directions for use, mixingreal guidance with elements of humor 704. The medical-inspiredalliteration and iconography are intended to invoke a sense ofprescriptive health care or wellness.

FIGS. 15 and 16 are a representative screen shot depicting an exemplaryuser interface in accordance with an aspect of the invention. As shownon FIG. 15, once the EMS (regimen) is defined and a particular course oftreatment (message) is started, on the top-right portion of the nextcard explicitly identifies the specific drug benefit 802. While notshown, by tapping the drug abbreviation, users can see the source ofsupporting scientific research 802. By tapping the hamburger icon, userscan choose to save the individual card, or share the card and itscontents with friends across social media. It is to be understood by aperson of ordinary skill in the art that these icons, or any icons, onthis card (window), or any card (window), may be positioned elsewhere(or anywhere), without departing from the inventive scope.

As shown on FIGS. 15 and 16, the focal point of the card (window) is theactual EMS-defined message (treatment), and in the case of this window,is a suggested action—jump for 5 seconds. FIG. 15 represents anexemplary card formatted for a mobile phone, while FIG. 16 represents anexemplary card formatted for a smart watch. Jumping for 5 seconds is asuggested action to restore the oxytocin neurotransmitter, which isdocumented for building happiness and confidence—the initially chosenEMS or behavioral intervention by the user (FIG. 13). The veracity ofthe message or suggested action is supported by the referencedpeer-reviewed research and co-signed credentialed expert 802. As aperson, skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the embodiments of the cards, windows, icons, designelements, EMS types, behavioral intervention types, message types,without departing from the scope of this invention as defined in thefollowing claims.

While not shown in FIGS. 15 and 16, the messages (cards/windows) maycomprise a single or battery of physical and, or cognitive tasks andbased on responses, further indicate a more nuanced EMS for a moretailored initial or subsequent message. Responses may include a level ofcompliance, engagement, interaction, choices, etc. Furthermore, fordeeper and more nuanced EMS definition, assigning an indication score orcolor-coded range to further convey EMS severity may be achievable. As aresult, matching of message type to scored or color-coded EMS mayproduce a more refined match for pushing of even more personalizeddigital content or therapeutics.

FIG. 17 illustrates a block diagram representing a system including themood mapper module 308 in relation to the EMS store and prescribers inaccordance with an aspect of the invention. In combination, the systemenables a specific sub-routine that ultimately provisions a dynamicassessment of a user's EMS (dEMS) based on a multi-correlate coordinatesystem (mood map). FIG. 18 illustrates a graphical representation of themood map including the at least two correlates of behavior(active/passive 902; positive/negative 904) underlying the user-plottedassessment of behavior in accordance with an aspect of the invention.The mood map allows users to plot as a single point along at least twocorrelates of behavior—resulting in a push of hyper-personalized digitalcontent with therapeutic value to reinforce or counter the user-mappeddynamic assessment.

In a preferred embodiment, as demonstrated in FIG. 17/18, the systemfeaturing a user-plotted mood map for deriving a dEMS for ahyper-personalized digital therapeutic comprises a message prescriber305, 307; an EMS store 303; a processor coupled to a memory elementstored with instructions, said processor when executing saidmemory-stored instructions, configure a mood mapping module (moodmapper) 308 to cause display of a coordinate-based sentiment valuespectrum (mood map) comprising one positive to negative-scaled axis 904and one perpendicular active to passive scaled axis 902 forming atwo-dimensional plot of a sentiment value along a positive to negativeline (positivity correlate) and an active to passive line (activitycorrelate); at least one user-plotted point on the displayed mood map toreflect a two-dimensional EMS (dynamic EMS) along the two correlates ofpositivity and activity, said dynamic EMS indicating a granularassessment of at least one of a feeling, sensation, mood, mental state,emotional condition, or physical status of the user; and the messageprescriber 305, 307 delivering at least a primary-level message (digitaltherapeutic) personalized to the user based on at least one of a storedmessage coupled to the dynamic EMS (hyper-personalized digitaltherapeutic).

In alternative embodiments, the mood map may comprise at least threeaxis in a three-dimensional representation, wherein one axis representsthe positivity correlate; the second axis the activity correlate; andthe third axis a time or duration correlate. In yet other embodiments,any type of correlates of behavior along any number of axis may berepresented to capture a dEMS based on a user-plot on the mood map.

FIG. 17 illustrates an exemplary processing unit with at least a oneprescriber 305 configured for displaying interactively therapeuticcontent from an EMS store 303 based on a user-plotted dEMS(hyper-personalized digital therapeutics). As shown, the system maycomprise an EMS store 303; at least a primary message prescriber 305; aprocessor coupled to a memory element with instructions, the processorwhen executing said memory-stored instructions, configure the system tocause: at least one EMS from a plurality of EMS in the EMS store 303 tobe pushed based on the user-plotted point, and alternatively, thedynamic sentiment value represented by the user-plotted point based onthe intersecting correlates of behavior.

While not shown in FIG. 17, any number of EMS or EMS types may beincluded in the EMS store 303. Each EMS may indicate at least one of afeeling, sensation, type of discomfort, mood, mental state, emotionalcondition, physical status of the user, and, or a behavioralintervention or training regimen. Any number of messages orinteractively therapeutic content may be associated with each EMS type.Each message; or interactively therapeutic content; or pushedtherapeutic may contain at least one of a text, image, sound, video, artasset, suggested action or recommended behavior. The matching ofmessage; interactively therapeutic content; or pushed therapeutic withEMS type may be pre-defined by at least one of an accredited expert orsource; probabilistic; or deep learned. In a preferred embodiment, anaccredited expert or source will require at least two independentsources of peer-reviewed scholarship or data in order to validate thematch.

The at least primary message prescriber 305 may push a message orinteractively therapeutic content hyper-personalized to the user basedon at least one stored message matched to the selected EMS. For example,within the EMS store 303, if EMS 1 (amused) is selected as plotted inthe far bottom left corner (FIG. 18, 115 c) the by the user, any one ofmessage 1, 2 . . . n may be selected by the prescriber 305. Thepre-defined messages validated by the accredited expert may all bemessages with documented utility in elevating mood and energy(counter-effect) or playful, light-hearted (reinforcing). The effectsdocumented for each message may be on a scale. For instance, EMS 1message 1 may be low-moderate; EMS 1/message 2 may be moderate; and EMS1/message n may be high-severe, etc. EMS types or message types may becolor coded or scored to indicate severity. Any variant of the scale maybe featured without departing from the scope of the invention. In otherembodiments, the messages, while falling under the same rubric andun-scaled, can vary along design cues. For instance, the prescriber 305may choose EMS 1/message 2, over other available messages, due to thefact that the message is comprised of traditionally feminine cues(pink-colored bauhaus typeface) for a female user. Other user profile,demographic information, or contextual information may further informthe prescribers 305 choice of message type, such as age, educationlevel, voting preference, etc. User profile or demographic informationmay be user inputted, digitally crawled, sensed or captured.

Still in reference to FIG. 17, the prescriber's 305 choice of messagetype may not specific to a user, user profile, or crawled user data. Ina certain embodiment, the prescriber 305 may have to choose between anyone of the message types (message 1, message 2 . . . message n) from theselected EMS type. This type of message assignment may be completelyarbitrary. In other embodiments, the message assignment may be notspecific to a user-generated or crawled profile but may be based on userhistory. In other words, a user's tracked level of engagement with aprevious message or message from a previous session may inform messageassignment by the prescriber 305. Tracking engagement of a user with apushed or prescribed therapeutic message may be by camera-captured eyegazing, touch-screen interaction, time span between pushed therapeuticand user follow-up action, choice of follow-up action, etc.

In some embodiments, the full list of message types is not grouped byEMS type or along any design categories, but rather simply listedarbitrarily and mapped or matched to an appropriate EMS type. In thisarbitrarily listed manner, the prescriber 305 may match to more than oneEMS type. Likewise, a user may be defined by more than one EMS type andbe prescribed the same message type. For instance, as illustrated inFIG. 18, a plot may indicate for an intermediary EMS between astonishedand indifferent 115 d or between sad and mad 115 e. In such an example,two EMS types may be diagnosed/assigned. Message types may be prescribedsuited for the intermediary EMS diagnosis. For example, in the case ofthe intermediary astonished/indifferent, the plot point may indicatethat the user is stronger leaning towards astonished than indifferent,and as a result, exclude certain message types associated with thetraditional indifferent EMS type. In other embodiments, the mood mappermodule 308 can take the coordinate position of each plot, calculate aprecise position, and plot the positon on the dynamic sentiment valuespectrum, wherein every coordinate position correlates with a preciseEMS. Precise EMS types may be on a scale or depicted with certainleanings/dispositions toward a specific correlate or other EMS types.

FIGS. 19A-19D are exemplary screen shots of the mood map interface inaccordance with an aspect of the invention. In FIG. 19A, the mood mapsx-axis is an activity correlate represented as an ocean surfacehorizontally bisecting the display, whereby a wave action increases thefurther right or left from a center point and the wave action calmsfurther left or right from the center point. The mood maps y-axis is apositivity correlate represented as a sky above the ocean surface andocean depth below the ocean surface, whereby the sky light becomesbrighter (indicating positivity) the further up from the center pointand the ocean depth becomes dimmer (indicating negativity) the furtherdown from the center point (FIGS. 19B, 19C, 19D).

While not illustrated, in some embodiments, the mood maps z-axis is atime or duration correlate, wherein the mood map shifts ninety degreesto reveal a side-sectional view of the ocean surface and shore, wherebythe shore at either end of the display represents day zero and time orduration increases the further from the shore. Other correlates ofbehavior may be represented on any one of the two or three axis of themood map, without departing from the scope of the invention.

The mood map/mapper may allow for a user to plot a single point on thex/y or x/y/z map, wherein each axis represents a unique andcomplementary behavioral attribute. In other embodiments, the user mayplot multiple points on the x/y or x/y/z map to provide at least fourbehavioral attributes to inform a dEMS assessment by creating acoefficient, which may be eventually converted into at least one of adEMS score, dEMS behavioral characteristic, d/EMS type, neurotransmitterimplicated, treatment regimen, digital therapeutic type, etc. In otherembodiments, at least one of a dEMS score, dEMS behavioralcharacteristic, d/EMS type, neurotransmitter implicated, treatmentregimen, or digital therapeutic type may be derived without the need ofa coefficient or algorithmically, statistically, probabilistically, ordeep learned.

In yet other embodiments, the user may engage the mood map/mood mapperby finger-tip scrolling across the map and removing the finger topinpoint the exact location of the circle/cursor point to define the atleast two-axis correlates of behavior. In other embodiments, the usermay finger-tip scroll across the map and double-tap to pinpoint theexact location of the circle/cursor point.

While not illustrated, in some embodiments, the mood map/mood mapper maybe configured in alternate ways to interactively engage the user indefining the user's dEMS. For instance, in one embodiment, themap/mapper may may be an interface comprising a series of verticallyoriented scales requiring the user to slide a bar up or down the scalein response to a question designed to infer wholly or partially a dEMSof the user. For instance, “what is the likelihood of the polar ice capscompletely melting by 2050?” The user would be prompted to slide the barin response to the question, wherein the furthest top of the scalerepresents an extremely high likelihood and the furthest bottom of thescale represents an extremely low likelihood. Questions may extend toquestions of a more personal nature, such as, “do you believe you willlose your patience, exhibited by an outburst of some kind, during thecourse of the work day today?” The system may capture the responses toeach of the questions and create a coefficient, which may be eventuallyconverted into at least one of a dEMS score, dEMS behavioralcharacteristic, d/EMS type, neurotransmitter implicated, treatmentregimen, digital therapeutic type, etc. In other embodiments, at leastone of a dEMS score, dEMS behavioral characteristic, d/EMS type,neurotransmitter implicated, treatment regimen, or digital therapeutictype may be derived without the need of a coefficient oralgorithmically, statistically, probabilistically, or deep learned.

FIG. 20A and FIG. 20B are exemplary screen shots of thehyper-personalized digital therapeutic pushed to the user-plotted dEMS.Once the EMS (regimen) is defined and a particular course of treatment(message) is started, the first card (window) explicitly identifies thespecific EMS and its associated neurotransmitter/effects. While notshown, by tapping the specific EMS and its associatedneurotransmitter/effects, users can see the source of supportingscientific research. By tapping the hamburger icon, users can choose tosave the individual card, or share the card and its contents withfriends across social media. It is to be understood by a person ofordinary skill in the art that these icons, or any icons, on this card(window), or any card (window), may be positioned elsewhere (oranywhere), without departing from the inventive scope.

The focal point of the same or next card (window) in series is theactual EMS-defined message (treatment), and in the case of this window,a suggested action—to plan a day outdoors with a friend. This suggestedaction is to restore/maintain/improve on the dynamic EMS of happiness byexpanding on the associated serotonin neurotransmitter, which isdocumented for building happiness and confidence. The veracity of themessage or suggested action is supported by the referenced peer-reviewedresearch and co-signed credentialed expert. As a person skilled in theart will recognize that modifications and changes can be made to theembodiments of the cards, windows, icons, design elements, EMS types,behavioral intervention types, message types, without departing from thescope of this invention.

While not shown in FIGS. 20A and 20B, the messages (cards/windows) maycomprise a single or battery of physical and, or cognitive tasks andbased on responses, further indicate a more nuanced EMS for a moretailored initial or subsequent (secondary) message. Responses mayinclude a level of compliance, engagement, interaction, choices, etc.Secondary messages may be pushed from secondary prescribers or primaryprescribers coupled to the EMS store. Furthermore, for deeper and morenuanced EMS definition, assigning an indication score or color-codedrange to further convey EMS severity may be achievable. As a result,matching of message type to scored or color-coded EMS may produce a morerefined match for pushing of even more personalized digital content ortherapeutics to boost mood, alleviate anxiety, reduce stress, andimprove psychological health or mental fitness by directing users tofollow procedures proven to increase the production of beneficialmolecules and neurotransmitters like Dopamine, Oxytocin, Acetylcholine,Serotonin, and GABA to deliver positive mood and mind-altering effects.

FIG. 21 illustrates a method flow chart for generating thehyper-personalized digital therapeutic pushed to the user-plotteddynamic EMS. The first step is: selecting at least one EMS for the userbased on a user-plotted point on a displayed mood map to reflect atleast a two-dimensional EMS along at least two correlates of behavior,said EMS indicating a granular assessment of at least one of a feeling,sensation, mood, mental state, emotional condition, or physical statusof the user 1008; and step two entails delivering at least aprimary-level message (digital therapeutic) personalized to the userbased on at least one of a stored message coupled to the EMS 1009.

FIG. 22 illustrates a method flow chart for delivering an audio-basedcontent (digital therapeutic or digital pharmaceutical) in accordancewith an aspect of the invention. In a preferred embodiment, the methodfor delivering an audio-based digital therapeutic entails the steps of:(1) selecting at least one EMS for the user, in which the EMS indicatesa granular assessment of at least one of a feeling, sensation, mood,mental state, emotional condition, or physical status of the user 1102;(2) choosing an audio-based digital therapeutic personalized to the userbased on at least one of a stored message coupled to the selected EMS1104; and finally (3) delivering said audio-based digital therapeutic toat least one of a user's device (mobile device, wearable, smart watch,tablet, desktop, laptop, headphones, or speaker) or home entertainmentsystem in communication with at least one of the user's device or avoice-activated Internet-of-Things (IoT) hub 1106.

In a preferred embodiment, the audio-based digital therapeutic is atleast one of a suggestion or recommendation for the user to perform atask or consume content with clinically proven benefits to address atleast one of a mood, anxiety, stress, psychological state, emotionalstate, or physical state by altering levels of at least oneneurotransmitter of the user. The content is tailored to alter at leastone neurotransmitter comprised of at least one of Dopamine, Serotonin,Epinephrine, Endorphins, Norepinephrine, Endorphins, Adrenaline,Oxytocin, or GABA.

In one instance, a user-plotted or user-selected EMS on a smart watch orsmart phone-configured interface may prompt a tailored curativeaudio-based content to be played-back via a users home entertainmentsystem coupled to a home automation (IoT) hub (in turn, coupled to theusers device and application. The user-plotted point may be on a one,two, or three dimensional circumplex-type graph (mood map or mood wheel)appearing on a smart-watch or mobile-phone configured interface. Theuser-selected EMS may be selected from a finger-scroll on a mobile-phonescreen or smart watch. The user-selected EMS may also be selected by ascroll of a dial disposed on the side of a smart-watch. Furthermore, thecontent may be further annotated with efficacy and dosage labels. Forinstance, two distinct contents may be tailored to alter Dopamine levelsin a user that has been assigned (diagnosed) with an EMS ofdepression/lethargy. However, since user 1 has been assigned (diagnosed)with a higher severity, user 1 may be delivered content specific to theEMS with a higher dosage and efficacy, versus the content delivered touser 2, who is experiencing a less severe form of depression/lethargy.An example of content with a higher dosage/efficacy may be content witha longer duration (120 seconds, versus 90 seconds, for instance) and, orcontent eliciting a stronger emotional response or a request to complywith a more strenuous physical task.

In another embodiment, the method may entail the steps of: (1) selectingat least one EMS for the user based on a user-plotted point on adisplayed mood map to reflect at least a two-dimensional EMS along atleast two correlates of behavior, said EMS indicating a granularassessment of at least one of a feeling, sensation, mood, mental state,emotional condition, or physical status of the user; (2) selecting anaudio-based digital therapeutic personalized to the user based on atleast one of a stored message coupled to the EMS; and (3) deliveringsaid audio-based digital therapeutic to at least one of a user's device(mobile device, wearable, smart watch, tablet, desktop, laptop) or homeentertainment system in communication with at least one of the user'sdevice or a voice-activated Internet-of-Things (IoT) hub.

In yet another embodiment, the method may entail discerning at least oneEMS for at least one user from a user-plotted point along a color wheel(mood wheel). In such an embodiment, the EMS may be selected/discernedby plotting a point on a perimeter of a displayed color wheel (moodwheel) comprising a gradient of colors, wherein each color is associatedwith a different EMS. The mood wheel may comprise two axis, wherein thefirst axis (outer perimeter of wheel) represents a first correlate ofbehavior, and the second axis (outer perimeter extending radiallytowards a center of the wheel) represents a second correlate ofbehavior. The plotted point represents two correlates of behavior thatinform an EMS specific or hyper-personalized to the user. Theuser-plotted point on the mood wheel may displayed on the users devicevia an application interface. Preferably, the mood wheel may bedisplayed on an interface configured for small-form factor user devices,such as a smart watch, and the like. Given the small display/interfaceas a function of the small-form factor of a smart watch, otheruser-plotted methods/devices, such as the mood map, may not bepreferable, although still used if necessary or preferred. In yet otherembodiments, the EMS may be defined based on at least one of a stored,previous user-plotted point on the mood wheel, or previous selected EMS.In still yet other embodiments, the EMS may be selected by the user froma list/store of EMS—or from a list/store of EMS with a preview ofassociated content. Other embodiments may include discerning theappropriate EMS for a user based on vocal attributes or speechrecognition.

It is preferable for the EMS to be discerned by a mood map, typicallydisplayed on a users device, such as a smart phone. The mood maps x-axisis an activity correlate represented as an ocean surface horizontallybisecting the display, whereby a wave action increases the further rightor left from a center point and the wave action calms further left orright from the center point. The mood maps y-axis is a positivitycorrelate represented as a sky above the ocean surface and ocean depthbelow the ocean surface, whereby the sky light becomes brighter(indicating positivity) the further up from the center point and theocean depth becomes dimmer (indicating negativity) the further down fromthe center point (FIGS. 19B, 19C, 19D).

While not illustrated, other mood maps may be possible to discern adynamic EMS, other than the animated ocean interface. In one embodiment,the x-axis may be at least one of an activity correlate or positivitycorrelate, different from the y-axis. For instance, the x-axis may be apositivity correlate, while the y-axis may be either an activitycorrelate or even a time correlate. In another embodiment, the x-axismay be an activity correlate, while the y-axis may b either a positivitycorrelate or time correlate. Any possible configuration of axis andbehavior correlates may be possible. The x-axis may be represented as agradient of one color, while the y-axis may be represented as a gradientof another color.

While also not illustrated, in some embodiments, the mood maps z-axis isa time or duration correlate, wherein the mood map shifts ninety degreesto reveal a side-sectional view of the ocean surface and shore, wherebythe shore at either end of the display represents day zero and time orduration increases the further from the shore. Other correlates ofbehavior may be represented on any one of the two or three axis of themood map, without departing from the scope of the invention.

The mood map/mapper may allow for a user to plot a single point on thex/y or x/y/z map, wherein each axis represents a unique andcomplementary behavioral attribute. In other embodiments, the user mayplot multiple points on the x/y or x/y/z map to provide at least fourbehavioral attributes to inform a dEMS assessment by creating acoefficient, which may be eventually converted into at least one of adEMS score, dEMS behavioral characteristic, d/EMS type, neurotransmitterimplicated, treatment regimen, digital therapeutic type, etc. In otherembodiments, at least one of a dEMS score, dEMS behavioralcharacteristic, d/EMS type, neurotransmitter implicated, treatmentregimen, or digital therapeutic type may be derived without the need ofa coefficient or algorithmically, statistically, probabilistically, ordeep learned.

In yet other embodiments, the user may engage the mood map/mood mapperor mood wheel by finger-tip scrolling across the map/wheel and removingthe finger to pinpoint the exact location of the circle/cursor point todefine the at least two-axis correlates of behavior. In otherembodiments, the user may finger-tip scroll across the map/wheel anddouble-tap to pinpoint the exact location of the circle/cursor point. Inother embodiments, at least one of a dEMS score, dEMS behavioralcharacteristic, d/EMS type, neurotransmitter implicated, severity,treatment regimen (duration/efficacy), or digital therapeutic type maybe derived algorithmically, statistically, probabilistically, or deeplearned.

While not shown, a system for delivering a digital therapeutic, specificto a users emotional or mental state (EMS) is also provided. The systemmay comprise: a primary message prescriber; a processor coupled to amemory element with instructions, said processor when executing saidmemory-stored instructions, configure the system to cause: at least oneEMS to be selected for the user, said EMS indicating a granularassessment of at least one of a feeling, sensation, mood, mental state,emotional condition, or physical status of the user; and the messageprescriber delivering an audio-based digital therapeutic personalized tothe user based on at least one of a stored message coupled to the EMS.

In some embodiments, the EMS is selected from at least one of alist/store from the user, by a mood map, or a mood wheel. Otherembodiments for ascertaining/discerning/diagnosing an EMS may bepossible, for instance, by vocal/speech recognition, or based on a userresponse from a single or series of diagnostic questions.

In some embodiments, once the EMS is diagnosed for user 1, an option mayexist for user 1 to forward to at least a user 2. In other embodiments,the message prescriber may deliver an audio-based digital therapeutic toat least a second user based on a request by a first user, withoutperforming an EMS diagnostic. In some embodiments, the audio-baseddigital therapeutic requested or selected is to be consumed (dosed)simultaneously by the first and at least the second user, wherein thefirst and second user are at least one of co-located or remotelylocated. For instance, after user 1 is diagnosed with adepression/lethargic EMS based on a user 1-plotted mood map, the messageprescriber may push an audio content tailored for combatting thediagnosed EMS. User 1 may then have the option to forward to at least auser 2 for simultaneous consumption, despite user 1 and user 2 beingcontinents apart. Simultaneous consumption providing for an enhanced ormore rewarding effect due to the understanding that another person ofyour choosing is experiencing the same emotional cues at exactly thesame time. In some embodiments, a pause in the playback from one of theusers may cause a pause in the playback of the other user involved inthe simultaneous consumption/dosing. For instance, upon user 1 receivinga call, the playback of the content is interrupted for both user 1 anduser 2 simultaneously, until user 1 is ready to resume consumption. Therequested, selected, or system diagnosed EMS and associated content(audio-based or visual-based) may be forwarded, simultaneously casted,separately casted, or simultaneously paused during interruption and onlyresumed upon either, or both, users ready for consumption.

While also not shown, in another embodiment, a system for delivering anidentical digital therapeutic to at least two users, specific to atleast a first and second user's emotional or mental state (EMS) may beprovided. The system may comprise: a primary message prescriber; aprocessor coupled to a memory element with instructions, wherein theprocessor when executing said memory-stored instructions, configure thesystem to cause: at least one EMS to be selected for at least the firstuser and the second user, wherein the EMS indicates a granularassessment of at least one of a feeling, sensation, mood, mental state,emotional condition, or physical status of the at least two users. Themessage prescriber may deliver the identical digital therapeuticpersonalized to the at least first and second user based on at least oneof a stored message coupled to the EMS and the identical digitaltherapeutic configured for at least one of a simultaneous playback orpause from the at least first and second users.

In some embodiments, the two users may be in a shared network or may becompletely independent of each other. Once simultaneousdosing/consumption (of the audio or visual-based content) is complete,the two users may wish to further engage in simultaneous consumption ofrelated content (audio-based or visual-based). Moreover, once the singleor serial consumption is complete, a messaging platform may allow forthe free exchange of communication between the two users. The platformor the system may also allow for the free exchange of othermedia—related or unrelated to the initial or subsequent single or serialconsumption.

Map engagement and hyper-personalized digital therapeutic content may bepushed to any number of user devices, such as a smart phone, smartwatch, tablet, smart tv, or any device with a display feature. DynamicEMS (dEMS) assessment via the mood map and content pushing may berendered/delivered identically across the ecosystem of devices. In otherembodiments, the rendering/delivery may be specifically formatted basedon the device form factor/configurations. For instance, a smart watchformat may alter the map presentation, plot mechanisms, and EMS store.The pushed content on a smaller form factor, such as a smart watch, mayfeature more text-based, static imagery, haptic effects, as opposed tolong-form animated or video content. Another user device may feature theuse of a home automation vocal-based hub, configured to recognizenatural based language input and output. In such embodiments, dEMS maybe rendered from vocal tone or responses to targeted question/s. Inother embodiments, dEMS may be user-selected. The hyper-personalizeddigital therapeutic in response to the rendered or user-selected dEMSmay be an audio output of a select EMS type from an audio-based EMSstore. The audio output may comprise at least one of a narrative, sound,song, tune, voice message, etc.

The claimed invention leverages existing clinical research and provenscience (already published in peer-reviewed journals) and repackagesinsights as content modules or behavioral interventions that aresimpler, more seductive, and profoundly more fun than traditionalanalogue therapies or digital treatment regimen. Described more simply,the system and platform curates existing digital content, and createsentirely new content programs, informed by and centered aroundtechniques proven to boost mood, alleviate anxiety, reduce stress, andimprove psychological health or mental fitness by directing users tofollow procedures proven to increase the production of beneficialmolecules and neurotransmitters like Dopamine, Oxytocin, Acetylcholine,Serotonin, and GABA to deliver positive mood and mind-altering effects.This is, in essence, a purely digital, transorbital drug deliverysystem. No pills. No powders. Purely digital experiences to positivelyimpact mood, mind and personal sense of well-being.

Now in reference to FIG. 23A. FIG. 23A illustrates an exemplary systemblock diagram of the GCT delivery in accordance with an aspect of theinvention. Illustrated is a preferred embodiment for a method fordelivering generalized clinician tips (GCT), specific to a usersemotional or mental state (EMS). In this preferred embodiment, themethod comprises the steps of: fast-capturing of at least one EMS forthe user based on at least one of a user-plotted point on at least oneof a displayed mood map 1204 or mood wheel or user-selected from a menu.The EMS indicating an assessment of at least one of a feeling,sensation, mood, mental state, emotional condition, or physical statusof the user. In other embodiments, the fast-capture also will ascribe(prescribe) the appropriate neurotransmitter (NT) associated with theuser-selected EMS that requires addressing. By limiting the EMS to aspecific handful of NT's, the assessment will be also fast-captured,rather than subjecting the user to the “paradox of choices”. ExemplaryNT's are Epinephrine, Norepinephrine, Endorphins, Acetylcholine,Dopamine, Serotonin, GABA, or Oxytocin—each NT corresponding to a uniqueEMS or a plurality of EMS. Conversely, an EMS may correspond to a uniqueNT or a plurality of NT's. Other NT's may be included beyond the NT'smentioned above.

Still in reference to FIG. 23A, delivering the GCT to at least one of auser's device (mobile device, wearable, smart watch, tablet, desktop,laptop, headphones, speaker, or smart speaker) or home entertainmentsystem in communication with at least one of the user's device or avoice-activated Internet-of-Things (IoT) hub; and wherein the GCT isselected from a store of EMS-specific GCT 1202 and is at least one of asuggestion or recommendation for the user to perform a task withclinical-consensus benefits to address at least one of the EMS and/orNT. The GCT is a long-form, text-based medium with substantiveclinician-approved recommendations or suggestions. The GCT may becoupled with visual assets or design elements, but the at the forefrontwill be the clinician-approved suggestions or recommendations in textform. It a suggestion or recommendation that has a consensus of at leasttwo accredited clinicians. The intended response from the GCT is toprimarily deliver a longitudinal behavioral response, such as helpingsomeone quitting a vice, re-engaging with an estranged family member, orimproving focus at the workplace, etc. Alternatively, the GCT may alsobe designed or peer-reviewed by a team of clinicians to deliver a moreacute response. For instance, the GCT may be a shorter-form text ofsuggestions or recommendations to perform a task to address the assessedEMS and/or NT. An example of this would be a suggestion to stop currentactivity and walk around the block, while taking deep breaths andholding before exhaling. The GCT may go on further explaining thebenefits of walking and deep breathing and how it elevates levels ofOxytocin, which is crucial for a sense of well-being and confidence.This type of short-form GCT, in contrast to the long-form, may beprescriptive for achieving an acute psychological or behavioralresponse, rather than a more longitudinal behavioral modification.

The GCT contrasts the short-burst digital therapeutic replete withdesign or visual assets. The short-burst digital therapeutic is a moresocial-based content intended to be fun and engage the user over a shortspan. The short-burst digital therapeutic or social-based digitalcontent (sdc) may also comprise of a short recommendation or suggestionintended to achieve an acute psychological response by altering NTlevels corresponding to the EMS selected.

In a preferred embodiment, the EMS may be defined based on auser-plotted or selected EMS. Alternatively, the EMS may be based on atleast one of a stored or previous user-plotted or selected EMS. In orderto achieve a fast-capture of EMS, at least one of the displayed mood mapor mood wheel may be used. As described earlier, the mood map or wheelreflects at least one of a two-dimensional or three-dimensional EMSalong at least two correlates of behavior. In alternate embodiments, athird correlate of behavior may be included, wherein the threecorrelates are a positivity correlate, an activity correlate, and a timecorrelate—for a more refined assessment.

As shown, the EMS may be further defined by the user answering curatedquestions and based on the answer (2^(nd) tier-assessment 1206), the GCTis further limited from a subset of the GCT store 1202. In otherembodiments, the 2^(nd)-tier assessment 1206 may be achieved by trackinga user performance to at least one of physical or cognitive task. In yetother embodiments, the 2^(nd)-tier assessment 1206 may be achieved bycapturing or tracking a biometric measurable from the user.

In another embodiment, subsequent or series of GCT may be deliveredbased on at least one of the users measured or self-reported response tothe first delivered GCT. For instance, an image, acoustic, heart rate,sweat, skin galvanic response capture means may be used to capture ormeasure a response to a first or prior GCT. Based on the measurable orresponse, a subsequent or series of GCT may be delivered accordingly. Inone example, a user receives a recommendation for the benefits ofconsistent exercise on mental health and immediately displaysmicro-gestures suggesting an unwillingness. Based on the capturedgestures, the subsequent or series of GCT will revise the recommendationto for a less strenuous activity, such as simply walking around theblock.

Now in reference to FIG. 23B, which is an exemplary method flow chart ofthe GCT delivery in accordance with an aspect of the invention. Themethod for delivering generalized clinician tips (GCT), specific to ausers emotional or mental state (EMS), the method comprising the stepsof: (1) fast-capturing of at least one EMS for the user based on atleast one of a user-plotted point on at least one of a displayed moodmap or mood wheel or user-selected from a menu, said EMS indicating anassessment of at least one of a feeling, sensation, mood, mental state,emotional condition, or physical status of the user and categorized asat least one of Dopamine, Serotonin, Epinephrine, Norepinephrine,Acetylcholine, Oxytocin, or GABA neurotransmitters 1302; (2) deliveringsaid GCT to at least one of a user's device (mobile device, wearable,smart watch, tablet, desktop, laptop, headphones, speaker, or smartspeaker) or home entertainment system in communication with at least oneof the user's device or a voice-activated Internet-of-Things (IoT) hub1304; and (3) delivering said GCT from a subset of the GCT store basedon the further defined EMS, wherein the GCT is selected from a store ofEMS-specific GCT and is at least one of a suggestion or recommendationfor the user to perform a task with clinical-consensus benefits toaddress at least one of the EMS and improve at least one of theassociated neurotransmitters 1306.

In other embodiments, the user may perform at least one of answering atleast one question, performing a physical task, conducting a cognitivetask, or subjecting to at least one biometric measurable via aninterface/sensor/capturing means to further define the at least one ofthe EMS and the at least one of the associated neurotransmitters(2^(nd)-tier assessment). The further defined EMS and/orneurotransmitter may deliver a more precisely tailored GCT specific tothe users needs. In yet other embodiments, the delivered GCT may becoupled with delivery of of at least one SDC. The SDC may be at leastone of serial or parallel with the GCT. In other words, once the GCT isdelivered, the at least one SDC may follow. Alternatively, the SDC andGCT may overlap/split a screen or screen-in-screen, analogous topicture-in-picture (PIP). In other embodiments, the SDC may premiere,followed by the GCT in any of the above mentioned screeningconfigurations or sequences. In an embodiment, a communication modulemay deliver and, or display at least one of the GCT from at least one ofa GCT store, GCT store subset, or SDC based on at least one of the EMSand/or NT.

Furthermore, in some embodiments, at least one of the GCT orsocial-based digital content is augmented by a member of a trustedshared network for further sharing within the network or to any of asocial media site. The member of the trusted shared network may beenabled to suggest or push social-based digital content outside of theEMS store. Furthermore, the SDC may further comprise pushing at leastone of a curated social media, news, sports feed based on the selectedEMS and/or NT specific for the user.

Now in reference to FIG. 24—depicting an exemplary method flow diagramdetailing the steps involved in the delivery of an encoded EMS(emotional or mental state) profile or encoded mood profile to a userdevice. The encoded EMS profile or encoded mood profile may also be aprofile based on digital content consumed (digital content/media diet).In one embodiment, a method for delivering an encoded digital contentprofile of a user to a device may comprise the steps of: determining thedigital content profile of the user based on digital content tracked1402; encoding a visual representation of the digital content profile torender an encoded digital content profile 1404; and delivering theencoded digital content profile to a device, wherein the encoded digitalcontent profile comprises of at least one of a colored or sized shapedelivered to the device in at least one of a logged-off, locked, orresting state 1406. The digital content tracked may be any and alldigital content viewed on all user devices—across any and all platforms.Alternatively, the digital content tracked may be content viewed on aspecific application or platform. Moreover, the tracking may simply becontent played partially or completely, or more heavily rate for contentthat is interacted with by the user, such as forwarded or re-played.

The tracking may be achieved by any of the conventional methods known inthe art, such as those used for developing marketing metrics.Alternatively, content—at the point of generation or curation—may bemetadata tagged with a specific content identifier that may bereferenced using a standardized look-up customized for EMS or NT(neurotransmitter) identification. As a result, content consumption fora user in a given period may be aggregated and parsed for EMS/NT type.The next step would be rating the parsed EMS/NT type and apportioning acolor, a color intensity, or shape in a visual representation for devicedisplay. The overall visual map representing an encoded EMS or moodprofile of the user based on his or her current or historicalmedia/digital content consumption. Any number of other techniques fortracking content, such as crawling or fingerprinting, may be used togenerate the encoded EMS or mood profile.

In another embodiment, the EMS or mood may be determined or assessedbased on any number of other factors besides digital content viewed. Forinstance, an EMS or mood may be determined based on a recent or previousinput of EMS/NT type by the user. Additionally, the EMS/NT type may beassessed based on a biometric or motion capture of the user. Leveragingan image capture or motion capture means of a device may allow thesystem to assess the user EMS/mood to generate the encoded profile fordevice display. While not shown in FIG. 24, a method for delivering anencoded emotional or mental state (EMS) profile of a user to a userdevice may comprise the steps of determining the EMS of the user basedon at least one of a sensor-captured, data gathered, or previouslyuser-selected input; and delivering an encoded visual representation ofsaid EMS to a user device in at least one of a lock-screen or reststate.

Any number of conventional routines may be employed to instruct a deviceprocessor to display the encoded profile, as opposed to any one of thefactory-set choices of screen-savers or lock-screen. In someembodiments, the EMS/mood profile may superimpose key information fromfactory-set screen, such as time, date, or temperature. The advantage ofthis profile serving as the rest or lock-screen on any device is that itis yet another fast-capture of the user mood snapshot pervasivelydisplayed, without the need of the user to log in or access theapplication. It serves as a pervasive reminder to the user of the usermood, EMS, or media/content diet—allowing the user to make betterinformed decisions. These decisions may range from work-place and socialinteractions, to media consumption habits and social media posts. Theprofile may additionally inform the user of a more accurate assessmentof EMS/NT for user input into the application for a better matcheddigital content pushed.

While also not illustrated in FIG. 24, the profile may be pushed in atleast one of a static, dynamic, or scheduled fashion. While not loggedon to the application, the profile may be pushed as or after content isviewed (dynamic fashion). Moreover, the profile may be pushed in ascheduled fashion, as per the scheduler preferences of the user. Forinstance, a user may prefer a profile sent three times a day,interspersed evenly, say at 11 am, 5 pm, and 11 pm. The static fashionis in reference to the system pushing the profile for display upon adevice being in a rest or lock state. Any one of the dynamic or staticfashion may also encompass for pushing a profile upon a triggered deviceor user event. For instance, a device event may be when the devicetransitions into a lock or rest state (screen-save), at which point apush of the profile as a rest or lock-screen is triggered. An example ofa user event triggering a profile push may be when the user reaches hisor her milestone of 10,000 steps or upon reaching a limit of 3 hoursspent on social media.

FIGS. 25 and 26 both illustrate an exemplary encoded profile asdisplayed on a smart phone and smart watch in accordance with an aspectof the invention. Each figure represents a different encoded profile, asdepicted by the variation in the visual representation between FIG. 25and FIG. 26. As depicted in FIGS. 25 and 26, the visual representationis primarily composed of a series of conjoined, separated, oroverlapping circles of varying sizes and colors. Any standardized rulemay be used to decode the representation. Moreover, any standardizedtable of colors and symbols representing EMS or NT may be used forapplication of the rule.

In one embodiment, based on the total time of a user viewingcontent—across the primary device or across any and all devices (tablet,phone, smart watch, home hub, speakers)—the EMS or NT type of thecontent will be captured and indicate the overall chemical footprint orexposure profile of the user via the encoded profile. As illustrated inFIGS. 25 and 26, the encoded profile is displayed on each of a smartphone or smart watch. As shown in both figures, the circles are ofvarying size and shape.

REPRESENTATIVE TABLE OF COLOR/SYMBOLS

Dopamine/associated EMS—Purple;

Endorphins/EMS—Red;

Testosterone/EMS—Klein Blue;

Oxytocin/EMS—Pink;

Acetylcholine/EMS—Green;

GABA/EMS—Light Blue;

Serotonin/EMS—Yellow;

Experimental Medicine/EMS—Hot Pink

It should be appreciated that any combination of EMS/NT andcolors/symbols may be paired. For instance, Dopamine may be representedas purple or as a purple square. This purple square may additionally bedisplayed on any generated, curated, or uploaded content as a way tolabel the content with a digital nutrition label. In the context ofFIGS. 25 and 26, circles are used as a fixed symbol and EMS/NT aredistinguished purely on a color basis. Likewise, the encoded profile maybe composed of colored shapes to distinguish EMS/NT, or simply as blankshapes.

In both figures, the colored circles appear in various sizes—indicatinga percentage of total time spent consuming or exposed to content of aparticular labeled EMS/NT. In other embodiments, the encoded profile maybe based on a sensor-captured input or a user input to denote a currentor a rolling profile of a user EMS/mood. As shown in FIG. 25, thepredominant circle displayed is green 1502 corresponding to Acetycholine(ACh) based on our representative color/symbol table, followed by yellow1504 corresponding to Serotonin (5-HT3). ACh is a neurotransmitter thathas been known to be associated with higher cognitive functioning, suchas focusing. ACh is the NT corresponding to the EMS or mood related tofocus or addressing a need to focus more. Based on a representative rulefor decoding colors/symbols, the large green circle 1502 may indicate toa user that the assessed or determined EMS of the user or trackedcontent of the user implicates the NT ACh and the EMS of focus. As aresult, a user may heed the indication and be more mindful of off-lineinteractions, on-line interactions, or future consumption of content.The user may be nudged to be less absent-minded during his or herday-to-day activities, as well as consciously consume content or make anactive effort to only consume content labeled with ACh (greenhalf-circle). Alternatively, the large green circle 1502 prominentlydisplayed on ones encoded profile may nudge the user to actively avoidany content labeled as ACh, since the profile already indicates a highlevel of focus or tracked content implicating focus.

In contrast, FIG. 26 shows an encoded profile featuring a large yellowcircle 1602 indicative of the EMS/NT of Serotonin/Happiness. Serotonin(5-HT3) is the NT associated with feelings of well-being and happiness.The inhibition of serotonin (5-HT3) re-uptake is the pharmacologicalapproach to addressing clinical depression. As shown in FIG. 26, thelarge yellow circle 1602 may indicate to a user that the assessed ordetermined EMS of the user or tracked content of the user implicates theNT 5-HT3 and the EMS of happiness. As a result, a user may heed theindication and be more mindful of off-line interactions, on-lineinteractions, or future consumption of content. The user may be nudgedto be less pessimistic during his or her day-to-day activities, as wellas consciously consume content or make an active effort to only consumecontent labeled with Serotonin (yellow full-circle). Alternatively, thelarge yellow circle 1602 prominently displayed on ones encoded profilemay nudge the user to actively avoid any content labeled with Serotonin(yellow full-circle), since the profile already indicates a high levelof happiness or tracked consumption of content implicating happiness.

In some embodiments, another rule for decoding may be provided, in whichin addition to color and size, placement on the screen may imply asignificance. Placement on the screen may confer a qualitative value forEMS/NT intensity, as opposed to just duration of consumption. Forinstance, a small yellow circle in the center of the encoded profile maysuggest that while the user has consumed content labeledSerotonin/5-HT3/Happiness for a short duration, the content consumed wasintense. An example of intense content may be a toddler riding the backof a large dog and chuckling uncontrollably. While the content wasshort, it was rated or labeled intensely for being strongly related toSerotonin/Happiness—hence the small yellow circle featured at the centerof the encoded profile. In contrast, a small yellow circle featured onthe margins of the encoded profile may suggest a short-duration of happycontent with low intensity. For instance, a quick glance of a picture ofan employee or acquaintance, who the user isn't exactly indifferenttowards, but who doesn't exactly invoke any overwhelmingly positivefeelings for the user either. This placement variable in the decodingrule may also apply to determined or assessed EMS/NT and not strictlyfor tracked digital content. The assessed or determined EMS/NT fromsensor-captured, data-gathered, or user-selected input may also drivethe specific placement of the colored shape/s to encode for intensity.

In another embodiment, the user may drag any one of the shapes to set apreferred EMS profile. This may result in a goal-set and notify the userof a degree of match with the dragged profile. In one embodiment, achange in profile over a time-at-a glance may be visually depicted witha time-lapse. In yet another embodiment, a user may be able to view hisor her profile or changes in his or her profile by time, day, or month.In another embodiment, a user may tap on any of the circles or shapes,revealing the total amount of EMS/NT content exposure.

Exposure may be expressed in terms of time exposed or percentage oftotal screen time—and may be displayed over the tapped circle, ordisplayed on a dedicated screen. Other embodiments enable a user to tapover any of the circles or shapes, resulting in a menu of content titlesor a thumbnail menu of content viewed corresponding to the coloredcircle or shape tapped. Additionally, the user may select any of thedrop-down menu titles or thumbnail menu content for preview or playback.

Profiles may additionally be displayed over a tablet or screenconfigured for display outside of an office or cubicle to fellowemployees/co-workers. This profile may help guide and better informoffice interactions and work-flow decisions, serving as a powerfulhuman-resource tool. Staff-wide management of work load may be achievedby a profile management program. For instance, if a manager detects aprofile indicative of focus-issues for a particular employee, themanager may then elect to relieve the employee of any attention-orientedtasks.

The profile may also be displayed on the outward-facing display of atwo-way or foldable smart phone or tablet. The profile may be a cue to aconcerned on-looker, friend, or family member for approaching andengaging in a social interaction or soft-intervention of sorts. On theother hand, an on-looker, friend, or family member may view the profileand provide much needed affirmation and support to the user.

Embodiments are described at least in part herein with reference toflowchart illustrations and/or block diagrams of methods, systems, andcomputer program products and data structures according to embodimentsof the disclosure. It will be understood that each block of theillustrations, and combinations of blocks, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general-purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner such that the instructions stored in the computer-readable memoryproduce an article of manufacture including instruction means whichimplement the function/act specified in the block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus, to produce a computer implemented process such that, theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions/acts specified inthe block or blocks.

In general, the word “module” as used herein, refers to logic embodiedin hardware or firmware, or to a collection of software instructions,written in a programming language, such as, Java, C, etc. One or moresoftware instructions in the unit may be embedded in firmware. Themodules described herein may be implemented as either software and/orhardware modules and may be stored in any type of non-transitorycomputer-readable medium or other non- transitory storage elements. Somenon-limiting examples of non-transitory computer-readable media includeCDs, DVDs, BLU-RAY, flash memory, mobile device, remote device, and harddisk drive.

We claim:
 1. A method for delivering an encoded emotional or mentalstate (EMS) profile of a user to a user device off-application, saidmethod comprising the steps of: determining the EMS of the user based onat least one of a sensor-captured, data gathered, or user-selectedinput; and delivering an encoded visual representation of said EMS to auser device in at least one of static, dynamic, or scheduled fashionwhile the device is not logged in to the application.
 2. The method ofclaim 1, wherein the data gathered EMS is based on digital contentviewed on the user device.
 3. The method of claim 1, wherein thesensor-captured EMS is based on an extent of activity monitored.
 4. Themethod of claim 1, wherein the user-selected EMS is based on mostrecently inputted EMS by the user.
 5. The method of claim 1, wherein theencoded visual representation of the user EMS is at least one shape ofvarying size, color, or color intensity to denote EMS types or severityof EMS types.
 6. The method of claim 1, wherein the encoded visualrepresentation is a plurality of shapes of varying size, color, or colorintensity to denote EMS types or severity of EMS types.
 7. The method ofclaim 1, wherein placement of the shape on the visual representationdenote EMS types or severity of EMS types
 8. The method of claim 1,wherein at least one shape of varying size, color, or color intensitydenote EMS types or severity of EMS types, wherein the EMS types orseverity of EMS types is an indication of the user's current digitalcontent diet.
 9. The method of claim 1, wherein at least one shape ofvarying size, color, or color intensity denote a digital content diet ofat least one of a current diet or historical diet.
 10. The method ofclaim 1, wherein overlapping of shapes denote digital contentcorresponding to more than one EMS types.
 11. The method of claim 1,wherein proximal placement of shapes denote different and relateddigital content, wherein each of the different content have a unique EMStype.
 12. The method of claim 1, wherein the profile is delivered in astatic fashion, wherein the static fashion is at least one of a fixedincrement of time or a fixed event.
 13. The method of claim 1, whereinthe profile is delivered in a dynamic fashion based on at least one ofan updated EMS, recently viewed content, or content being currentlyviewed.
 14. The method of claim 1, wherein the scheduled fashion ofprofile delivery is based on a users preference for at least one of atime or format preferences.
 15. The method of claim 1, wherein theoff-application is in reference to the user device being logged-off theapplication.
 16. A method for delivering an encoded emotional or mentalstate (EMS) profile of a user to a user device, said method comprisingthe steps of: determining the EMS of the user based on at least one of asensor-captured, data gathered, or previously user-selected input; anddelivering an encoded visual representation of said EMS to a user devicein at least one of a lock-screen or rest state.
 17. The method of claim16, wherein the user may drag any one of the shapes to set a preferredEMS profile.
 18. The method of claim 17, wherein a notification ispushed indicating degree of match with the preferred EMS profile. 19.The method of claim 16, wherein a change in profile over a time-at-aglance is visually depicted with a time-lapse.
 20. A method fordelivering an encoded digital content profile of a user to a device,said method comprising the steps of: determining the digital contentprofile of the user based on digital content tracked; encoding a visualrepresentation of the digital content profile to render an encodeddigital content profile; and delivering the encoded digital contentprofile to a device, wherein the encoded digital content profilecomprises of at least one of a colored or sized shape delivered in atleast one of a static, dynamic, or scheduled fashion.
 21. The method ofclaim 20, wherein the device is at least one of smart phone, smartwatch, tablet, television, laptop, desktop, or home entertainment hub.22. The method of claim 20, wherein the device is at least one of atablet or screen display configured for display in or out of at leastone of an office or cubicle.
 23. The method of claim 20, wherein thedevice is a screen display configured for public display.
 24. The methodof claim 20, wherein the device is a foldable smart phone configured foroutward display of the profile.
 25. The method of claim 24, wherein theoutward display causes a further digital interaction.
 26. A method fordelivering an encoded digital content profile of a user to a device,said method comprising the steps of: determining the digital contentprofile of the user based on digital content tracked; encoding a visualrepresentation of the digital content profile to render an encodeddigital content profile; and delivering the encoded digital contentprofile to a device, wherein the encoded digital content profilecomprises of at least one of a colored or sized shape delivered to thedevice in at least one of a logged-off, locked, or resting state.